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] hf download RESMP-DEV/LFM2.5-Encoder-230M-Code-MXFP4-GPTQ --local-dir LFM2.5-Encoder-230M-Code-MXFP4-GPTQ
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download tokenizer_config.json from RESMP-DEV/LFM2.5-Encoder-230M-Code-MXFP4-GPTQ: direct link, hf CLI and curl.
- Browser
- Download file 334 Bytes
-
https://huggingface.co/RESMP-DEV/LFM2.5-Encoder-230M-Code-MXFP4-GPTQ/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://RESMP-DEV/LFM2.5-Encoder-230M-Code-MXFP4-GPTQ/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/RESMP-DEV/LFM2.5-Encoder-230M-Code-MXFP4-GPTQ/resolve/main/tokenizer_config.json
334 Bytes
| { | |
| "backend": "tokenizers", | |
| "bos_token": "<|startoftext|>", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|im_end|>", | |
| "is_local": true, | |
| "local_files_only": false, | |
| "mask_token": "<|mask|>", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<|pad|>", | |
| "tokenizer_class": "TokenizersBackend" | |
| } | |