Feature Extraction
MLX
Safetensors
muse_glimmer
mlx-vlm
metaencoder
multimodal
embeddings
quantized
8-bit precision
Instructions to use edgefloor/meta-encoder-mlx-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use edgefloor/meta-encoder-mlx-8bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download edgefloor/meta-encoder-mlx-8bit --local-dir meta-encoder-mlx-8bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download tokenizer.json from edgefloor/meta-encoder-mlx-8bit: direct link, hf CLI and curl.
- Browser
- Download file 28.1 MB
-
https://huggingface.co/edgefloor/meta-encoder-mlx-8bit/resolve/main/tokenizer.json
- Command line
-
hf download hf://edgefloor/meta-encoder-mlx-8bit/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/edgefloor/meta-encoder-mlx-8bit/resolve/main/tokenizer.json
28.1 MB
- Xet hash:
- f89930c709b5f7103e260b59259e1197c070b4905f44d102d859b81c3d662f83
- Size of remote file:
- 28.1 MB
- SHA256:
- c9dbee66967b58f31a7c27f723c3760da3526ccd0427578e8905b0abb0031c4d
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