Average Word Embeddings Glove.6B.300d

1
6.0B
license:apache-2.0
by
DataikuNLP
Embedding Model
OTHER
6B params
New
0 downloads
Early-stage
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Edge AI:
Mobile
Laptop
Server
14GB+ RAM
Mobile
Laptop
Server
Quick Summary

This model is a copy of this model repository from sentence-transformers at the specific commit `5d2b7d1c127036ae98b9d487eca4d48744edc709`.

Device Compatibility

Mobile
4-6GB RAM
Laptop
16GB RAM
Server
GPU
Minimum Recommended
6GB+ RAM

Code Examples

Usage (Sentence-Transformers)text
pip install -U sentence-transformers
Usage (Sentence-Transformers)text
pip install -U sentence-transformers
Usage (Sentence-Transformers)text
pip install -U sentence-transformers
Usage (Sentence-Transformers)text
pip install -U sentence-transformers
Usage (Sentence-Transformers)text
pip install -U sentence-transformers
Usage (Sentence-Transformers)text
pip install -U sentence-transformers
python
from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence", "Each sentence is converted"]

model = SentenceTransformer('sentence-transformers/average_word_embeddings_glove.6B.300d')
embeddings = model.encode(sentences)
print(embeddings)
python
from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence", "Each sentence is converted"]

model = SentenceTransformer('sentence-transformers/average_word_embeddings_glove.6B.300d')
embeddings = model.encode(sentences)
print(embeddings)
python
from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence", "Each sentence is converted"]

model = SentenceTransformer('sentence-transformers/average_word_embeddings_glove.6B.300d')
embeddings = model.encode(sentences)
print(embeddings)
python
from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence", "Each sentence is converted"]

model = SentenceTransformer('sentence-transformers/average_word_embeddings_glove.6B.300d')
embeddings = model.encode(sentences)
print(embeddings)
python
from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence", "Each sentence is converted"]

model = SentenceTransformer('sentence-transformers/average_word_embeddings_glove.6B.300d')
embeddings = model.encode(sentences)
print(embeddings)
python
from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence", "Each sentence is converted"]

model = SentenceTransformer('sentence-transformers/average_word_embeddings_glove.6B.300d')
embeddings = model.encode(sentences)
print(embeddings)

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