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Moriacrafter
/
Qwen-1.8B_DepressionDetection

Feature Extraction
Transformers
Safetensors
qwen
llama-factory
custom_code
Model card Files Files and versions
xet
Community

Instructions to use Moriacrafter/Qwen-1.8B_DepressionDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Moriacrafter/Qwen-1.8B_DepressionDetection with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="Moriacrafter/Qwen-1.8B_DepressionDetection", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("Moriacrafter/Qwen-1.8B_DepressionDetection", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
Qwen-1.8B_DepressionDetection
3.68 GB
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  • 1 contributor
History: 3 commits
Moriacrafter's picture
Moriacrafter
Upload tokenizer
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  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
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  • config.json
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  • configuration_qwen.py
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  • cpp_kernels.py
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  • generation_config.json
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  • model-00001-of-00004.safetensors
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    xet
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  • model-00002-of-00004.safetensors
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  • model-00003-of-00004.safetensors
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  • model-00004-of-00004.safetensors
    724 MB
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  • model.safetensors.index.json
    14.7 kB
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  • modeling_qwen.py
    55.6 kB
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  • qwen.tiktoken
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  • qwen_generation_utils.py
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  • special_tokens_map.json
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  • tokenization_qwen.py
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  • tokenizer_config.json
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