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mdizak
/
t5-conversation-summ-rust

Transformers
PyTorch
Rust
bart
text2text-generation
Generated from Trainer
Eval Results (legacy)
Model card Files Files and versions
xet
Community
1

Instructions to use mdizak/t5-conversation-summ-rust with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use mdizak/t5-conversation-summ-rust with Transformers:

    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("mdizak/t5-conversation-summ-rust")
    model = AutoModelForSeq2SeqLM.from_pretrained("mdizak/t5-conversation-summ-rust", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
t5-conversation-summ-rust
6.12 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 4 commits
mdizak's picture
mdizak
Vocab
0ef8c1e over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    1.93 kB
    Initial commit over 2 years ago
  • added_tokens.json
    75 Bytes
    Initial commit over 2 years ago
  • config.json
    1.59 kB
    Initial commit over 2 years ago
  • generation_config.json
    274 Bytes
    Initial commit over 2 years ago
  • merges.txt
    456 kB
    Initial commit over 2 years ago
  • model.npz
    2.24 GB
    xet
    Initial commit over 2 years ago
  • pytorch_model.bin
    1.63 GB
    xet
    Initial commit over 2 years ago
  • rust_model.ot
    2.24 GB
    xet
    Initial commit over 2 years ago
  • special_tokens_map.json
    167 Bytes
    Initial commit over 2 years ago
  • tokenizer.json
    2.11 MB
    Initial commit over 2 years ago
  • tokenizer_config.json
    1.25 kB
    Initial commit over 2 years ago
  • training_args.bin
    4.22 kB
    xet
    Initial commit over 2 years ago
  • vocab.json
    798 kB
    Initial commit over 2 years ago
  • vocab.txt
    232 kB
    Vocab over 2 years ago