slm-kk-pythia14m-dapt-13k

19
license:apache-2.0
by
saken-tukenov
Language Model
OTHER
New
19 downloads
Early-stage
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Quick Summary

AI model with specialized capabilities.

Training Data Analysis

🟢 Excellent (8.0/10)

Researched training datasets used by slm-kk-pythia14m-dapt-13k with quality assessment

Specialized For

code
general
science
multilingual

Training Datasets (1)

the pile
🟢 8/10
code
general
science
multilingual
Key Strengths
  • •Deliberate Diversity: Explicitly curated to include diverse content types (academia, code, Q&A, book...
  • •Documented Quality: Each component dataset is thoroughly documented with rationale for inclusion, en...
  • •Epoch Weighting: Component datasets receive different training epochs based on perceived quality, al...

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Code Examples

Usagepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("EleutherAI/pythia-14m")
model = AutoModelForCausalLM.from_pretrained("saken-tukenov/slm-kk-pythia14m-dapt-13k")

input_ids = tokenizer("Қазақстан — ", return_tensors="pt").input_ids
output = model.generate(input_ids, max_new_tokens=50, do_sample=True, temperature=0.8)
print(tokenizer.decode(output[0], skip_special_tokens=True))

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