Instructions to use RESMP-DEV/LFM2.5-Encoder-230M-Code-MXFP4-GPTQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use RESMP-DEV/LFM2.5-Encoder-230M-Code-MXFP4-GPTQ with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir LFM2.5-Encoder-230M-Code-MXFP4-GPTQ RESMP-DEV/LFM2.5-Encoder-230M-Code-MXFP4-GPTQ
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Xet hash:
- 7ff944419877a192762d292422a75cff5004bbbf34e81f2cf613ac51c864a790
- Size of remote file:
- 221 MB
- SHA256:
- c3c6540a9580560630ec5a5179c71872c16eff32f633e234114df814cb3a3a94
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