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ademax
/
metadata

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

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

  • Libraries
  • Transformers

    How to use ademax/metadata with Transformers:

    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("ademax/metadata")
    model = AutoModelForSeq2SeqLM.from_pretrained("ademax/metadata")
  • Notebooks
  • Google Colab
  • Kaggle
metadata
1.81 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 4 commits
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model
8ce7c15 verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • added_tokens.json
    2.93 kB
    Upload tokenizer over 2 years ago
  • config.json
    784 Bytes
    Upload T5ForConditionalGeneration over 2 years ago
  • generation_config.json
    142 Bytes
    Upload T5ForConditionalGeneration over 2 years ago
  • model.safetensors
    904 MB
    xet
    Adding `safetensors` variant of this model over 1 year ago
  • pytorch_model.bin
    904 MB
    xet
    Upload T5ForConditionalGeneration over 2 years ago
  • special_tokens_map.json
    2.49 kB
    Upload tokenizer over 2 years ago
  • spiece.model
    820 kB
    xet
    Upload tokenizer over 2 years ago
  • tokenizer.json
    2.42 MB
    Upload tokenizer over 2 years ago
  • tokenizer_config.json
    22.5 kB
    Upload tokenizer over 2 years ago