Any-to-Any
MLX
diffusion-lm
mixture-of-experts
multimodal
text-to-image
image-understanding
apple-silicon
llada
Instructions to use treadon/mlx-llada2-uni with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use treadon/mlx-llada2-uni with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir mlx-llada2-uni treadon/mlx-llada2-uni
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Upload pyproject.toml with huggingface_hub
Browse files- pyproject.toml +22 -0
pyproject.toml
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[build-system]
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requires = ["setuptools", "wheel"]
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build-backend = "setuptools.build_meta"
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[project]
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name = "mlx-llada2-uni"
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version = "0.0.1"
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description = "LLaDA2.0-Uni (diffusion LLM) on Apple Silicon via MLX"
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license = {text = "Apache-2.0"}
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requires-python = ">=3.10"
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dependencies = [
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"mlx>=0.20",
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"numpy",
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"huggingface_hub",
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"safetensors",
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"transformers",
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"tqdm",
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]
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[tool.setuptools.packages.find]
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where = ["."]
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include = ["llada2*"]
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