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sagawa
/
chemlm-86.24m

Transformers
PyTorch
bert
chemistry
smiles
molecular-property-prediction
masked-language-modeling
Model card Files Files and versions
xet
Community
1

Instructions to use sagawa/chemlm-86.24m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use sagawa/chemlm-86.24m with Transformers:

    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("sagawa/chemlm-86.24m", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
chemlm-86.24m
354 MB
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  • 1 contributor
History: 4 commits
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model
41f52b3 verified 10 days ago
  • .gitattributes
    1.52 kB
    initial commit 10 days ago
  • README.md
    7.66 kB
    Update README.md 10 days ago
  • args.json
    2.86 kB
    Upload 8 files 10 days ago
  • config.json
    742 Bytes
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  • deepspeed_config.json
    289 Bytes
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  • model.safetensors
    177 MB
    xet
    Adding `safetensors` variant of this model 10 days ago
  • pytorch_model.bin

    Detected Pickle imports (3)

    • "torch._utils._rebuild_tensor_v2",
    • "collections.OrderedDict",
    • "torch.BFloat16Storage"

    What is a pickle import?

    177 MB
    xet
    Upload 8 files 10 days ago
  • special_tokens_map.json
    695 Bytes
    Upload 8 files 10 days ago
  • tokenizer.json
    54 kB
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  • tokenizer_config.json
    1.37 kB
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  • vocab.json
    32.2 kB
    Upload 8 files 10 days ago