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jdchang
/
test_rm_small

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

Instructions to use jdchang/test_rm_small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use jdchang/test_rm_small with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="jdchang/test_rm_small", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("jdchang/test_rm_small", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
test_rm_small
717 MB
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  • 1 contributor
History: 3 commits
jdchang's picture
jdchang
Upload tokenizer
ee81922 verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • README.md
    5.17 kB
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  • config.json
    1.57 kB
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  • generation_config.json
    143 Bytes
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  • hf_utils.py
    11.4 kB
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  • model.safetensors
    708 MB
    xet
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  • special_tokens_map.json
    320 Bytes
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  • tokenizer.json
    9.09 MB
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  • tokenizer_config.json
    51.2 kB
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