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OmAhire369
/
safe-genai-reward-full

Text Classification
Transformers
Safetensors
bert
safety
alignment
preference-learning
reward
full
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use OmAhire369/safe-genai-reward-full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use OmAhire369/safe-genai-reward-full with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="OmAhire369/safe-genai-reward-full")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("OmAhire369/safe-genai-reward-full")
    model = AutoModelForSequenceClassification.from_pretrained("OmAhire369/safe-genai-reward-full", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
safe-genai-reward-full
439 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
OmAhire369's picture
OmAhire369
reward / full checkpoint
180cfb4 verified about 1 month ago
  • .gitattributes
    1.52 kB
    initial commit about 1 month ago
  • README.md
    1.9 kB
    reward / full checkpoint about 1 month ago
  • config.json
    757 Bytes
    reward / full checkpoint about 1 month ago
  • model.safetensors
    438 MB
    xet
    reward / full checkpoint about 1 month ago
  • special_tokens_map.json
    125 Bytes
    reward / full checkpoint about 1 month ago
  • tokenizer.json
    711 kB
    reward / full checkpoint about 1 month ago
  • tokenizer_config.json
    1.19 kB
    reward / full checkpoint about 1 month ago
  • training_meta.json
    1.3 kB
    reward / full checkpoint about 1 month ago
  • vocab.txt
    232 kB
    reward / full checkpoint about 1 month ago