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10ths
/
FADS_base_model

Feature Extraction
Transformers
Safetensors
xgenmm
custom_code
Model card Files Files and versions
xet
Community

Instructions to use 10ths/FADS_base_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use 10ths/FADS_base_model with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="10ths/FADS_base_model", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModelForVision2Seq
    model = AutoModelForVision2Seq.from_pretrained("10ths/FADS_base_model", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
FADS_base_model
9.18 GB
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  • 1 contributor
History: 4 commits
10ths's picture
10ths
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a5db0d0 verified almost 2 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • README.md
    5.17 kB
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  • added_tokens.json
    407 Bytes
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  • config.json
    873 Bytes
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  • generation_config.json
    147 Bytes
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  • model-00001-of-00002.safetensors
    4.98 GB
    xet
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  • model-00002-of-00002.safetensors
    4.2 GB
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  • model.safetensors.index.json
    66.7 kB
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  • preprocessor_config.json
    467 Bytes
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  • special_tokens_map.json
    1.09 kB
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  • tokenizer.model
    500 kB
    xet
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  • tokenizer_config.json
    4.21 kB
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