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pandalla
/
ChatLaw2-MoE

Feature Extraction
Transformers
Safetensors
internlm2
custom_code
Model card Files Files and versions
xet
Community
1

Instructions to use pandalla/ChatLaw2-MoE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use pandalla/ChatLaw2-MoE with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="pandalla/ChatLaw2-MoE", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("pandalla/ChatLaw2-MoE", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
ChatLaw2-MoE
440 kB
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  • 1 contributor
History: 2 commits
JessyTsu1's picture
JessyTsu1
Upload 13 files
f679eb2 verified almost 2 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • README.md
    31 Bytes
    initial commit almost 2 years ago
  • all_results.json
    168 Bytes
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  • config.json
    1.16 kB
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  • configuration_internlm.py
    7.39 kB
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  • generation_config.json
    132 Bytes
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  • model.safetensors.index.json
    48.2 kB
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  • modeling_internlm.py
    111 kB
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  • special_tokens_map.json
    713 Bytes
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  • tokenization_internlm2.py
    8.81 kB
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  • tokenizer.model
    132 Bytes
    xet
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  • tokenizer_config.json
    2.35 kB
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  • train_results.json
    168 Bytes
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  • trainer_state.json
    257 kB
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  • training_args.bin
    129 Bytes
    xet
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