Instructions to use MLXBits/sulphur-2-distill-mlx-q4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use MLXBits/sulphur-2-distill-mlx-q4 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir sulphur-2-distill-mlx-q4 MLXBits/sulphur-2-distill-mlx-q4
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
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# LTX2.3 Model Repository
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This repository hosts custom implementations of the LTX2.3 video AI model, refined specifically for high-fidelity generation using the Sulphur 2 architecture. It has been converted to Apples MLX architecture and quantized down to Q4, to maximize memory efficiency. It has been tested on a 32GB M5 Silicon Mac, and that is the lowest recommended RAM for this model.
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If you are not on a Mac, this madel variant is not for you.
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pipeline_tag: image-text-to-video
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---
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This repository hosts custom implementations of the LTX2.3 video AI model, refined specifically for high-fidelity generation using the Sulphur 2 architecture. It has been converted to Apples MLX architecture and quantized down to Q4, to maximize memory efficiency. It has been tested on a 32GB M5 Silicon Mac, and that is the lowest recommended RAM for this model.
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If you are not on a Mac, this madel variant is not for you.
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