Instructions to use RESMP-DEV/LFM2.5-Encoder-350M-MLX-FP32 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-MLX-FP32 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download RESMP-DEV/LFM2.5-Encoder-350M-MLX-FP32 --local-dir LFM2.5-Encoder-350M-MLX-FP32
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
File size: 259 Bytes
591cda4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | [project]
name = "lfm2-5-encoder-350m-mlx-fp32"
version = "0.1.0"
requires-python = ">=3.11"
dependencies = ["mlx==0.32.0"]
[project.optional-dependencies]
validate = [
"numpy==2.3.5",
"safetensors==0.8.0",
"torch==2.12.1",
"transformers==5.12.1",
]
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