Instructions to use RESMP-DEV/LFM2.5-Encoder-350M-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-350M-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-350M-Code-MXFP8-GPTQ RESMP-DEV/LFM2.5-Encoder-350M-Code-MXFP8-GPTQ
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Xet hash:
- 2e636136ccad9de2e87f7a38aa7f91a1292b735ee9abf833cb50453ed726de62
- Size of remote file:
- 431 MB
- SHA256:
- 79288c8d909bf8e3fc6034bf307a06443ed32d67fc61e41155fc7dd4f62568f4
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