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cointegrated
/
rut5-base

Transformers
PyTorch
JAX
Safetensors
Russian
English
multilingual
t5
text2text-generation
russian
text-generation-inference
Model card Files Files and versions
xet
Community
2

Instructions to use cointegrated/rut5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use cointegrated/rut5-base with Transformers:

    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("cointegrated/rut5-base")
    model = AutoModelForSeq2SeqLM.from_pretrained("cointegrated/rut5-base")
  • Notebooks
  • Google Colab
  • Kaggle
rut5-base
1.96 GB
Ctrl+K
Ctrl+K
  • 4 contributors
History: 6 commits
lbourdois's picture
lbourdois
Add multilingual to the language tag
111dcef over 3 years ago
  • .gitattributes
    736 Bytes
    allow flax almost 5 years ago
  • README.md
    806 Bytes
    Add multilingual to the language tag over 3 years ago
  • config.json
    664 Bytes
    The first commit about 5 years ago
  • flax_model.msgpack
    977 MB
    xet
    upload flax model almost 5 years ago
  • pytorch_model.bin
    977 MB
    xet
    The first commit about 5 years ago
  • special_tokens_map.json
    65 Bytes
    The first commit about 5 years ago
  • spiece.model
    828 kB
    xet
    The first commit about 5 years ago
  • tokenizer_config.json
    233 Bytes
    The first commit about 5 years ago