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NamCyan
/
Magicoder-S-DS-6.7B-technical-debt-code-tesoro

Text Classification
Transformers
Safetensors
llama
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use NamCyan/Magicoder-S-DS-6.7B-technical-debt-code-tesoro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use NamCyan/Magicoder-S-DS-6.7B-technical-debt-code-tesoro with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="NamCyan/Magicoder-S-DS-6.7B-technical-debt-code-tesoro")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("NamCyan/Magicoder-S-DS-6.7B-technical-debt-code-tesoro")
    model = AutoModelForSequenceClassification.from_pretrained("NamCyan/Magicoder-S-DS-6.7B-technical-debt-code-tesoro")
  • Notebooks
  • Google Colab
  • Kaggle
Magicoder-S-DS-6.7B-technical-debt-code-tesoro
26.4 GB
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  • 1 contributor
History: 7 commits
NamCyan's picture
NamCyan
Update README.md
f573303 verified over 1 year ago
  • .gitattributes
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    initial commit over 1 year ago
  • README.md
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  • added_tokens.json
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  • config.json
    751 Bytes
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  • model-00001-of-00006.safetensors
    4.84 GB
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  • model-00002-of-00006.safetensors
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  • model-00003-of-00006.safetensors
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  • model-00004-of-00006.safetensors
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  • model-00005-of-00006.safetensors
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  • model-00006-of-00006.safetensors
    2.16 GB
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  • model.safetensors.index.json
    23.9 kB
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  • special_tokens_map.json
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  • tokenizer.json
    1.37 MB
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  • tokenizer.model
    500 kB
    xet
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  • tokenizer_config.json
    5.06 kB
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