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RaushanTurganbay
/
kimi-two-layers

Feature Extraction
Transformers
Safetensors
kimi_k25
custom_code
Model card Files Files and versions
xet
Community

Instructions to use RaushanTurganbay/kimi-two-layers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use RaushanTurganbay/kimi-two-layers with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="RaushanTurganbay/kimi-two-layers", trust_remote_code=True)
    # Load model directly
    from transformers import AutoProcessor, AutoModel
    
    processor = AutoProcessor.from_pretrained("RaushanTurganbay/kimi-two-layers", trust_remote_code=True)
    model = AutoModel.from_pretrained("RaushanTurganbay/kimi-two-layers", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
kimi-two-layers
98 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 21 commits
RaushanTurganbay's picture
RaushanTurganbay HF Staff
Upload processor
56a2962 verified about 1 month ago
  • .gitattributes
    1.63 kB
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  • README.md
    5.17 kB
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  • chat_template.jinja
    4.02 kB
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  • config.json
    5.41 kB
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  • configuration_deepseek.py
    11.2 kB
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  • configuration_kimi_k25.py
    5.44 kB
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  • converted.pt
    40.8 GB
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  • converted.safetensors
    40.8 GB
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  • generation_config.json
    52 Bytes
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  • model.safetensors
    16.4 GB
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    Rename new_merged.safetensors to model.safetensors 3 months ago
  • modeling_deepseek.py
    78.5 kB
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  • modeling_kimi_k25.py
    51 kB
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  • processor_config.json
    2.74 kB
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  • tokenizer.json
    19.6 MB
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  • tokenizer_config.json
    462 Bytes
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