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rooftopcoder
/
t5-small-coqa

Transformers
PyTorch
TensorBoard
t5
text2text-generation
Generated from Trainer
text-generation-inference
Model card Files Files and versions
xet
Metrics Training metrics Community
1

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

  • Libraries
  • Transformers

    How to use rooftopcoder/t5-small-coqa with Transformers:

    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("rooftopcoder/t5-small-coqa")
    model = AutoModelForSeq2SeqLM.from_pretrained("rooftopcoder/t5-small-coqa")
  • Notebooks
  • Google Colab
  • Kaggle
t5-small-coqa
245 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 46 commits
rooftopcoder's picture
rooftopcoder
librarian-bot's picture
librarian-bot
Librarian Bot: Add base_model information to model (#1)
1e107a9 almost 3 years ago
  • runs
    End of training about 3 years ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • .gitignore
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    Training in progress, step 500 about 3 years ago
  • README.md
    1.15 kB
    Librarian Bot: Add base_model information to model (#1) almost 3 years ago
  • all_results.json
    711 Bytes
    End of training about 3 years ago
  • config.json
    1.47 kB
    Training in progress, step 500 about 3 years ago
  • eval_results.json
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  • generated_predictions.txt
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  • generation_config.json
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  • predict_results.json
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  • pytorch_model.bin
    242 MB
    xet
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  • special_tokens_map.json
    2.2 kB
    Training in progress, step 500 about 3 years ago
  • spiece.model
    792 kB
    xet
    Training in progress, step 500 about 3 years ago
  • tokenizer.json
    2.42 MB
    Training in progress, step 500 about 3 years ago
  • tokenizer_config.json
    2.32 kB
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  • train_results.json
    196 Bytes
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  • trainer_state.json
    5.47 kB
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  • training_args.bin
    4.09 kB
    xet
    Training in progress, step 500 about 3 years ago