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summaria
/
qa-qg-t5

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

Instructions to use summaria/qa-qg-t5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use summaria/qa-qg-t5 with Transformers:

    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("summaria/qa-qg-t5")
    model = AutoModelForSeq2SeqLM.from_pretrained("summaria/qa-qg-t5", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
qa-qg-t5
895 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
avinash-vk's picture
avinash-vk
v1
6f728ef about 5 years ago
  • .gitattributes
    690 Bytes
    initial commit about 5 years ago
  • config.json
    1.39 kB
    v1 about 5 years ago
  • eval_results.txt
    30 Bytes
    v1 about 5 years ago
  • model_args.json
    2.6 kB
    v1 about 5 years ago
  • optimizer.pt
    2.14 MB
    xet
    v1 about 5 years ago
  • pytorch_model.bin
    892 MB
    xet
    v1 about 5 years ago
  • scheduler.pt
    623 Bytes
    xet
    v1 about 5 years ago
  • special_tokens_map.json
    1.79 kB
    v1 about 5 years ago
  • spiece.model
    792 kB
    xet
    v1 about 5 years ago
  • tokenizer_config.json
    2.15 kB
    v1 about 5 years ago
  • training_args.bin
    3.12 kB
    xet
    v1 about 5 years ago