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z-image-turbo MLX quant-matrix: q4/q8/bf16 tiers (sc-8670)

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.gitattributes CHANGED
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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ language:
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+ - en
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+ pipeline_tag: text-to-image
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+ library_name: mlx
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+ tags:
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+ - mlx
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+ - apple-silicon
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+ - diffusion
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+ - z-image
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+ - text-to-image
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+ - quantized
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+ base_model: Tongyi-MAI/Z-Image-Turbo
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+ ---
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+
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+ # Z-Image-Turbo — MLX quant-matrix (SceneWorks re-host)
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+
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+ Pre-built **MLX** (Apple Silicon) quantization tiers of [`Tongyi-MAI/Z-Image-Turbo`](https://huggingface.co/Tongyi-MAI/Z-Image-Turbo), hosted by [SceneWorks](https://github.com/SceneWorks) for direct, ready-to-run loading in the SceneWorks desktop app (no install-time conversion, no gated download).
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+
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+ ## Tiers
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+
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+ Each subdirectory is a complete, self-contained snapshot (transformer + Qwen3 text encoder + VAE + tokenizer + scheduler) that the SceneWorks `z_image_turbo` engine loads directly:
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+
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+ | Tier | Subdir | Precision | Use |
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+ |------|--------|-----------|-----|
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+ | Q4 (default) | `q4/` | 4-bit group-affine (group 64) weights; dense norms | smallest footprint |
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+ | Q8 | `q8/` | 8-bit group-affine weights | higher fidelity |
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+ | bf16 | `bf16/` | dense bf16 | maximum fidelity |
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+
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+ The transformer, text encoder, and VAE attention are quantized in the Q4/Q8 tiers; the bf16 tier is the full dense model. The packed weights auto-detect their quantization on load (no manifest needed).
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+
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+ ## License
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+
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+ Apache-2.0, inherited from the upstream `Tongyi-MAI/Z-Image-Turbo`. This is an unmodified-weights re-host (re-quantized for MLX). All credit to the Tongyi-MAI team.
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+ ]
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