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baseten
/
smol_llama-101M-GQAForSequenceClassification

Text Classification
Transformers
Safetensors
llama
text-embeddings-inference
Model card Files Files and versions
xet
Community
2

Instructions to use baseten/smol_llama-101M-GQAForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use baseten/smol_llama-101M-GQAForSequenceClassification with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="baseten/smol_llama-101M-GQAForSequenceClassification")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("baseten/smol_llama-101M-GQAForSequenceClassification")
    model = AutoModelForSequenceClassification.from_pretrained("baseten/smol_llama-101M-GQAForSequenceClassification")
  • Notebooks
  • Google Colab
  • Kaggle
smol_llama-101M-GQAForSequenceClassification
310 MB
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  • 1 contributor
History: 6 commits
michaelfeil's picture
michaelfeil
Update config.json
685d2c7 verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • README.md
    5.17 kB
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  • config.json
    852 Bytes
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  • model.safetensors
    306 MB
    xet
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  • special_tokens_map.json
    414 Bytes
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  • tokenizer.json
    3.62 MB
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  • tokenizer.model
    500 kB
    xet
    Upload tokenizer (#1) over 1 year ago
  • tokenizer_config.json
    990 Bytes
    Update tokenizer_config.json over 1 year ago