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RafatK
/
SMT-AZR

Feature Extraction
Transformers
Safetensors
seamless_m4t_v2
Model card Files Files and versions
xet
Community

Instructions to use RafatK/SMT-AZR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use RafatK/SMT-AZR with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="RafatK/SMT-AZR")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("RafatK/SMT-AZR")
    model = AutoModel.from_pretrained("RafatK/SMT-AZR")
  • Notebooks
  • Google Colab
  • Kaggle
SMT-AZR
9.28 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
RafatK's picture
RafatK
Upload processor
b259f3b verified 9 months ago
  • .gitattributes
    1.57 kB
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  • README.md
    5.17 kB
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  • added_tokens.json
    2.07 kB
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  • config.json
    2.71 kB
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  • generation_config.json
    9.91 MB
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  • model-00001-of-00002.safetensors
    5 GB
    xet
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  • model-00002-of-00002.safetensors
    4.24 GB
    xet
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  • model.safetensors.index.json
    211 kB
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  • preprocessor_config.json
    1.78 kB
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  • sentencepiece.bpe.model
    5.17 MB
    xet
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  • special_tokens_map.json
    2.34 kB
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  • tokenizer.json
    31.2 MB
    xet
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  • tokenizer_config.json
    19.7 kB
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