bge-code-v1

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42
2 languages
license:apache-2.0
by
BAAI
Embedding Model
OTHER
New
8K downloads
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Quick Summary

AI model with specialized capabilities.

Code Examples

Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
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git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagetext
git clone https://github.com/FlagOpen/FlagEmbedding.git
cd FlagEmbedding
pip install -e .
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
Usagepython
from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)

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