Instructions to use RESMP-DEV/LFM2.5-Encoder-230M-Code-MXFP8-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-MXFP8-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-MXFP8-GPTQ RESMP-DEV/LFM2.5-Encoder-230M-Code-MXFP8-GPTQ
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Xet hash:
- 784f76b2145b6c4f37ad13befbac70cdd2b753145a21c50d1d2e7255f20e69b1
- Size of remote file:
- 302 MB
- SHA256:
- 42b45915f2458b1ec551a2ac89133b7ae280a3203c62c13f91ce2ee3b1f2b9b3
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