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
- Atomic Chat
Download tokenizer.json from RESMP-DEV/LFM2.5-Encoder-230M-Code-MXFP4-GPTQ: direct link, hf CLI and curl.
- Browser
- Download file 4.73 MB
-
https://huggingface.co/RESMP-DEV/LFM2.5-Encoder-230M-Code-MXFP4-GPTQ/resolve/main/tokenizer.json
- Command line
-
hf download hf://RESMP-DEV/LFM2.5-Encoder-230M-Code-MXFP4-GPTQ/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/RESMP-DEV/LFM2.5-Encoder-230M-Code-MXFP4-GPTQ/resolve/main/tokenizer.json
4.73 MB
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