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liuda1
/
DeepSeek-R1-Distill-Qwen-32B-bnb-8bit

Feature Extraction
Transformers
Safetensors
qwen2
bnb-my-repo
text-embeddings-inference
4-bit precision
bitsandbytes
Model card Files Files and versions
xet
Community

Instructions to use liuda1/DeepSeek-R1-Distill-Qwen-32B-bnb-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use liuda1/DeepSeek-R1-Distill-Qwen-32B-bnb-8bit with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="liuda1/DeepSeek-R1-Distill-Qwen-32B-bnb-8bit")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("liuda1/DeepSeek-R1-Distill-Qwen-32B-bnb-8bit")
    model = AutoModel.from_pretrained("liuda1/DeepSeek-R1-Distill-Qwen-32B-bnb-8bit")
  • Notebooks
  • Google Colab
  • Kaggle
DeepSeek-R1-Distill-Qwen-32B-bnb-8bit
17.7 GB
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  • 1 contributor
History: 2 commits
liuda1's picture
liuda1
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  • model.safetensors.index.json
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  • tokenizer.json
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  • tokenizer_config.json
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