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jrahn
/
ROOK-CLF-9m

Text Classification
Transformers
Safetensors
English
llama
chess
classification
strategic-reasoning
reproduction
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use jrahn/ROOK-CLF-9m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use jrahn/ROOK-CLF-9m with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="jrahn/ROOK-CLF-9m")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("jrahn/ROOK-CLF-9m")
    model = AutoModelForSequenceClassification.from_pretrained("jrahn/ROOK-CLF-9m")
  • Notebooks
  • Google Colab
  • Kaggle
ROOK-CLF-9m
18 MB
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  • 1 contributor
History: 10 commits
jrahn's picture
jrahn
Update README.md
a02db44 verified 8 months ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • README.md
    6.97 kB
    Update README.md 8 months ago
  • config.json
    73.8 kB
    Upload TextClassificationPipeline over 1 year ago
  • model.py
    3.86 kB
    Upload tokenizer over 1 year ago
  • model.safetensors
    17.9 MB
    xet
    Upload TextClassificationPipeline over 1 year ago
  • special_tokens_map.json
    101 Bytes
    Upload TextClassificationPipeline over 1 year ago
  • tokenizer.json
    1.63 kB
    Upload TextClassificationPipeline over 1 year ago
  • tokenizer.py
    23.8 kB
    Upload TextClassificationPipeline over 1 year ago
  • tokenizer_config.json
    1.01 kB
    Upload TextClassificationPipeline over 1 year ago