Instructions to use anfedoro/bge-m3-mlx-fp16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use anfedoro/bge-m3-mlx-fp16 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir bge-m3-mlx-fp16 anfedoro/bge-m3-mlx-fp16
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
BGE-M3 MLX FP16
MLX FP16 format conversion of BAAI/bge-m3 at revision
5617a9f61b028005a4858fdac845db406aefb181. Converted on 2026-07-14T17:44:06.212531+00:00 with
scripts/convert_bge_m3_to_mlx_fp16.py. The backbone, sparse_linear, and
colbert_linear weights all come from that source revision. No additional
training was performed.
Target runtime: MLX. Target dtype: FP16. The source model license is MIT; see the upstream model card for its complete terms and attribution.
- Downloads last month
- 301
Model size
0.6B params
Tensor type
F16
·
Hardware compatibility
Log In to add your hardware
Quantized
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support
Model tree for anfedoro/bge-m3-mlx-fp16
Base model
BAAI/bge-m3