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FastFlowLM
/
Gemma3-4B-NPU2

Transformers
English
gemma3_text
unsloth
gemma3
gemma
google
Model card Files Files and versions
xet
Community

Instructions to use FastFlowLM/Gemma3-4B-NPU2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use FastFlowLM/Gemma3-4B-NPU2 with Transformers:

    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("FastFlowLM/Gemma3-4B-NPU2", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • Unsloth Desktop
Gemma3-4B-NPU2
4.78 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 13 commits
FastFlowLM's picture
FastFlowLM
Upload tokenizer_config.json
a5ad9db verified about 1 month ago
  • .gitattributes
    2.03 kB
    Init about 1 year ago
  • README.md
    21.9 kB
    Update README.md about 1 year ago
  • attn.xclbin
    465 kB
    xet
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  • config.json
    1.72 kB
    Upload 2 files about 1 month ago
  • dequant.xclbin
    115 kB
    xet
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  • layer.xclbin
    283 kB
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  • lm_head.xclbin
    153 kB
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  • mm.xclbin
    348 kB
    xet
    Init about 1 year ago
  • model.q4nx
    3.77 GB
    xet
    Fix RMS Norm Weights about 1 year ago
  • tokenizer.json
    33.4 MB
    xet
    Init about 1 year ago
  • tokenizer_config.json
    1.16 MB
    Upload tokenizer_config.json about 1 month ago
  • vision_attn.xclbin
    255 kB
    xet
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  • vision_mm.xclbin
    387 kB
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  • vision_weight.q4nx
    974 MB
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