Feature Extraction
MLX
Safetensors
ministral3
apple-silicon
quantized
mixed-precision
axquant
axq
development
mistral3
MXFP4
embedding
sentence-similarity
4-bit precision
Instructions to use AutomatosX/AX-Nemotron-3-Embed-1B-MLX-AXQ-MXFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use AutomatosX/AX-Nemotron-3-Embed-1B-MLX-AXQ-MXFP4 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download AutomatosX/AX-Nemotron-3-Embed-1B-MLX-AXQ-MXFP4 --local-dir AX-Nemotron-3-Embed-1B-MLX-AXQ-MXFP4
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download tokenizer.json from AutomatosX/AX-Nemotron-3-Embed-1B-MLX-AXQ-MXFP4: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/AutomatosX/AX-Nemotron-3-Embed-1B-MLX-AXQ-MXFP4/resolve/main/tokenizer.json
- Command line
-
hf download hf://AutomatosX/AX-Nemotron-3-Embed-1B-MLX-AXQ-MXFP4/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/AutomatosX/AX-Nemotron-3-Embed-1B-MLX-AXQ-MXFP4/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 2b52da05abaf03eeef07e9d892fc36cf0aac639f72814f6e470df48dcf2f81e9
- Size of remote file:
- 17.1 MB
- SHA256:
- 797410dfb649a5b9ba92bc4fef7dbf4022d00e73de6867c4ac199a8846439421
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