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jdchang
/
Meta-Llama-3-8B-Instruct-RM

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

Instructions to use jdchang/Meta-Llama-3-8B-Instruct-RM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use jdchang/Meta-Llama-3-8B-Instruct-RM with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="jdchang/Meta-Llama-3-8B-Instruct-RM", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("jdchang/Meta-Llama-3-8B-Instruct-RM", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
Meta-Llama-3-8B-Instruct-RM
32.2 GB
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  • 1 contributor
History: 2 commits
jdchang's picture
jdchang
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b3ca691 verified almost 2 years ago
  • .gitattributes
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  • README.md
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  • config.json
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  • generation_config.json
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  • model-00001-of-00007.safetensors
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  • model-00005-of-00007.safetensors
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  • model.safetensors.index.json
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  • modeling_hf.py
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