Sentence Similarity
MLX
Safetensors
multilingual
English
Chinese
xlm-roberta
mlx-embeddings
omlx
apple-silicon
m1
bge-m3
embeddings
feature-extraction
retrieval
rag
8-bit precision
Instructions to use YCF-AI/bge-m3-8bit-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use YCF-AI/bge-m3-8bit-MLX with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download YCF-AI/bge-m3-8bit-MLX --local-dir bge-m3-8bit-MLX
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download modules.json from YCF-AI/bge-m3-8bit-MLX: direct link, hf CLI and curl.
- Browser
- Download file 349 Bytes
-
https://huggingface.co/YCF-AI/bge-m3-8bit-MLX/resolve/main/modules.json
- Command line
-
hf download hf://YCF-AI/bge-m3-8bit-MLX/modules.json
-
curl -L -o modules.json https://huggingface.co/YCF-AI/bge-m3-8bit-MLX/resolve/main/modules.json
349 Bytes
| [ | |
| { | |
| "idx": 0, | |
| "name": "0", | |
| "path": "", | |
| "type": "sentence_transformers.models.Transformer" | |
| }, | |
| { | |
| "idx": 1, | |
| "name": "1", | |
| "path": "1_Pooling", | |
| "type": "sentence_transformers.models.Pooling" | |
| }, | |
| { | |
| "idx": 2, | |
| "name": "2", | |
| "path": "2_Normalize", | |
| "type": "sentence_transformers.models.Normalize" | |
| } | |
| ] |