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 1_Pooling/config.json from RESMP-DEV/LFM2.5-Encoder-230M-Code-MXFP4-GPTQ: direct link, hf CLI and curl.
- Browser
- Download file 298 Bytes
-
https://huggingface.co/RESMP-DEV/LFM2.5-Encoder-230M-Code-MXFP4-GPTQ/resolve/main/1_Pooling/config.json
- Command line
-
hf download hf://RESMP-DEV/LFM2.5-Encoder-230M-Code-MXFP4-GPTQ/1_Pooling/config.json
-
curl -L -o config.json https://huggingface.co/RESMP-DEV/LFM2.5-Encoder-230M-Code-MXFP4-GPTQ/resolve/main/1_Pooling/config.json
298 Bytes
| { | |
| "word_embedding_dimension": 1024, | |
| "pooling_mode_cls_token": false, | |
| "pooling_mode_mean_tokens": true, | |
| "pooling_mode_max_tokens": false, | |
| "pooling_mode_mean_sqrt_len_tokens": false, | |
| "pooling_mode_weightedmean_tokens": false, | |
| "pooling_mode_lasttoken": false, | |
| "include_prompt": true | |
| } | |