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Meta-Okapi
/
trained_reward_fr_lr3e-5_10ksteps

Text Classification
Transformers
Safetensors
bloom
Model card Files Files and versions
xet
Community

Instructions to use Meta-Okapi/trained_reward_fr_lr3e-5_10ksteps with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Meta-Okapi/trained_reward_fr_lr3e-5_10ksteps with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="Meta-Okapi/trained_reward_fr_lr3e-5_10ksteps")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("Meta-Okapi/trained_reward_fr_lr3e-5_10ksteps")
    model = AutoModelForSequenceClassification.from_pretrained("Meta-Okapi/trained_reward_fr_lr3e-5_10ksteps")
  • Notebooks
  • Google Colab
  • Kaggle
trained_reward_fr_lr3e-5_10ksteps
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  • 1 contributor
History: 4 commits
geronest's picture
geronest
Upload BloomForSequenceClassification
4b06947 verified 9 months ago
  • .gitattributes
    1.52 kB
    initial commit 9 months ago
  • README.md
    5.17 kB
    Upload BloomForSequenceClassification 9 months ago
  • config.json
    849 Bytes
    Upload BloomForSequenceClassification 9 months ago
  • generation_config.json
    132 Bytes
    Upload BloomWithLogitsToKeep 9 months ago
  • model.safetensors
    3.44 GB
    xet
    Upload BloomForSequenceClassification 9 months ago