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nicholasKluge
/
Harmless-RewardModel

Text Classification
Transformers
Safetensors
English
roberta
reward model
alignment
preference model
RLHF
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use nicholasKluge/Harmless-RewardModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use nicholasKluge/Harmless-RewardModel with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="nicholasKluge/Harmless-RewardModel")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("nicholasKluge/Harmless-RewardModel")
    model = AutoModelForSequenceClassification.from_pretrained("nicholasKluge/Harmless-RewardModel", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
Harmless-RewardModel
1.51 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 13 commits
nicholasKluge's picture
nicholasKluge
Update README.md
3cf2a1e verified about 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • LICENSE
    10.8 kB
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  • README.md
    8.84 kB
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  • config.json
    789 Bytes
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  • emissions.csv
    770 Bytes
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  • hh_rlhf_eval.parquet
    9.41 MB
    xet
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  • merges.txt
    456 kB
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  • model.safetensors
    499 MB
    xet
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  • optimizer.pt
    997 MB
    xet
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  • rng_state.pth
    14.2 kB
    xet
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  • scheduler.pt
    1.06 kB
    xet
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  • special_tokens_map.json
    280 Bytes
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  • tokenizer.json
    2.11 MB
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  • tokenizer_config.json
    1.22 kB
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  • trainer_state.json
    4.93 kB
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  • training_args.bin
    5.11 kB
    xet
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  • vocab.json
    798 kB
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