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sp-embraceable
/
Orpheus3BTTS-FT-Embraceable-Full_Dataset_5000steps

Feature Extraction
Transformers
Safetensors
llama
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use sp-embraceable/Orpheus3BTTS-FT-Embraceable-Full_Dataset_5000steps with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use sp-embraceable/Orpheus3BTTS-FT-Embraceable-Full_Dataset_5000steps with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="sp-embraceable/Orpheus3BTTS-FT-Embraceable-Full_Dataset_5000steps")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("sp-embraceable/Orpheus3BTTS-FT-Embraceable-Full_Dataset_5000steps")
    model = AutoModel.from_pretrained("sp-embraceable/Orpheus3BTTS-FT-Embraceable-Full_Dataset_5000steps")
  • Notebooks
  • Google Colab
  • Kaggle
Orpheus3BTTS-FT-Embraceable-Full_Dataset_5000steps
13.2 GB
Ctrl+K
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  • 1 contributor
History: 3 commits
sp-embraceable's picture
sp-embraceable
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  • .gitattributes
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  • README.md
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  • config.json
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  • model-00001-of-00003.safetensors
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  • model-00003-of-00003.safetensors
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  • model.safetensors.index.json
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  • special_tokens_map.json
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  • tokenizer.json
    22.8 MB
    xet
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  • tokenizer_config.json
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