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eprasad
/
distilled-t5-small

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

Instructions to use eprasad/distilled-t5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use eprasad/distilled-t5-small with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="eprasad/distilled-t5-small")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("eprasad/distilled-t5-small")
    model = AutoModelForSequenceClassification.from_pretrained("eprasad/distilled-t5-small")
  • Notebooks
  • Google Colab
  • Kaggle
distilled-t5-small
2.16 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
eprasad's picture
eprasad
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f8b70e0 verified 11 months ago
  • autotrain-data
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  • checkpoint-1875
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  • .gitattributes
    1.52 kB
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  • README.md
    572 Bytes
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  • config.json
    976 Bytes
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  • merges.txt
    466 kB
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  • model.safetensors
    538 MB
    xet
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  • special_tokens_map.json
    977 Bytes
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  • tokenizer.json
    3.52 MB
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  • tokenizer_config.json
    3.75 kB
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  • training_args.bin
    5.78 kB
    xet
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  • training_params.json
    868 Bytes
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  • vocab.json
    801 kB
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