Instructions to use kruatech/studio-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use kruatech/studio-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download kruatech/studio-mlx --local-dir studio-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download shared/qwen3-4b-text-encoder/tokenizer/tokenizer.json from kruatech/studio-mlx: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/kruatech/studio-mlx/resolve/main/shared/qwen3-4b-text-encoder/tokenizer/tokenizer.json
- Command line
-
hf download hf://kruatech/studio-mlx/shared/qwen3-4b-text-encoder/tokenizer/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/kruatech/studio-mlx/resolve/main/shared/qwen3-4b-text-encoder/tokenizer/tokenizer.json
11.4 MB
- Xet hash:
- 693ec4b3922b0bd306bf7b4989e115ffbfeb7b0c08b31bc6d956818c6bb07f61
- Size of remote file:
- 11.4 MB
- SHA256:
- aeb13307a71acd8fe81861d94ad54ab689df773318809eed3cbe794b4492dae4
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