Feature Extraction
MLX
Safetensors
muse_glimmer
mlx-vlm
metaencoder
multimodal
embeddings
quantized
4-bit precision
Instructions to use edgefloor/meta-encoder-mlx-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use edgefloor/meta-encoder-mlx-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download edgefloor/meta-encoder-mlx-4bit --local-dir meta-encoder-mlx-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download source-sha256.json from edgefloor/meta-encoder-mlx-4bit: direct link, hf CLI and curl.
- Browser
- Download file 215 Bytes
-
https://huggingface.co/edgefloor/meta-encoder-mlx-4bit/resolve/main/source-sha256.json
- Command line
-
hf download hf://edgefloor/meta-encoder-mlx-4bit/source-sha256.json
-
curl -L -o source-sha256.json https://huggingface.co/edgefloor/meta-encoder-mlx-4bit/resolve/main/source-sha256.json
215 Bytes
| { | |
| "model-00002-of-00002.safetensors": "ced1649f8cf4ab4852f68fad42656a60022a9271b4319a606534f5ff03ca3aca", | |
| "model-00001-of-00002.safetensors": "b1479b3c58364b9135e28ccac7b6dd5e99482662f4a3ce82cae5ef25f819d6f7" | |
| } | |