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Amalq
/
clinical_t5_final_taskA

Transformers
PyTorch
t5
text2text-generation
text-generation-inference
Model card Files Files and versions
xet
Community
1

Instructions to use Amalq/clinical_t5_final_taskA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Amalq/clinical_t5_final_taskA with Transformers:

    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("Amalq/clinical_t5_final_taskA")
    model = AutoModelForSeq2SeqLM.from_pretrained("Amalq/clinical_t5_final_taskA")
  • Notebooks
  • Google Colab
  • Kaggle
clinical_t5_final_taskA
2.68 GB
Ctrl+K
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  • 1 contributor
History: 7 commits
Amalq's picture
Amalq
Upload pytorch_model.bin
5ad7819 about 3 years ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • config.json
    781 Bytes
    Upload 2 files about 3 years ago
  • generation_config.json
    142 Bytes
    Upload 2 files about 3 years ago
  • optimizer.pt
    1.78 GB
    xet
    Upload optimizer.pt about 3 years ago
  • pytorch_model.bin
    892 MB
    xet
    Upload pytorch_model.bin about 3 years ago
  • special_tokens_map.json
    2.2 kB
    Upload 3 files about 3 years ago
  • tokenizer.json
    2.42 MB
    Upload 3 files about 3 years ago
  • tokenizer_config.json
    2.39 kB
    Upload 3 files about 3 years ago
  • trainer_state.json
    1.46 kB
    Upload trainer_state.json about 3 years ago
  • training_args.bin
    3.63 kB
    xet
    Upload training_args.bin about 3 years ago