Instructions to use codeclawd/refine-qwen3-1.7b-6bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use codeclawd/refine-qwen3-1.7b-6bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download codeclawd/refine-qwen3-1.7b-6bit --local-dir refine-qwen3-1.7b-6bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Mirror of PrivateWhisper/refine-qwen3-1.7b-6bit at revision fe5cd8d3fd45cb3594bbd6b7b16f918a62d2ce21, kept by the PrivateWispr team as a backup host. Licence: not declared upstream; the model is a LoRA-fine-tuned, 6-bit MLX quantization of Qwen3-1.7B (Apache-2.0), and the Qwen3 licence applies. Original authors: the PrivateWispr team (the model was trained for PrivateWispr, a local dictation app for macOS).
The weights, tokenizer and config files in this repo are byte-identical to the upstream revision above. Only this README was added.
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Model size
2B params
Tensor type
U32
·
BF16 ·
Hardware compatibility
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6-bit
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