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Simplify headings and consolidate repeated project links

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  1. README.md +4 -6
README.md CHANGED
@@ -57,12 +57,12 @@ This published example uses the prompt **“add blue sunglasses.”**
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  Inpaint HQ uses the **full Stable Diffusion 1.5 inpainting denoiser** with Clover's
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  text encoder, tokenizer, VAE, and scheduler. It is a larger model than the compact
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- [regular Clover text-to-image checkpoint](https://huggingface.co/neonforestmist/Clover-Image-Tiny). Regular Clover generates from text; Inpaint HQ requires an image and mask.
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  On the release's 24-edit held-out evaluation, HQ improved masked prompt alignment by
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  **4.8%** and reduced masked target error by **11.1%** versus the previous Clover inpainting
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  release. These are evaluation-set results; individual edits still depend on the image,
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- mask, and prompt. [See the full quality gate and selection record](https://huggingface.co/neonforestmist/Clover-Image-Tiny-Inpaint/blob/main/docs/MODEL_DETAILS.md).
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  ## Run an edit with Python
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@@ -109,13 +109,13 @@ precision, and dependencies can change the result even with the same seed.
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  ## Styles and Apple devices
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- The [Clover iOS app](https://github.com/neonforestmist/Clover-Image-Tiny-iOS) provides a native masking workflow.
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  Core ML resources are published [separately](https://huggingface.co/neonforestmist/Clover-Image-Tiny-Inpaint-CoreML).
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  Published Clover attention-only LoRAs are mechanically compatible in Diffusers,
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  but they were trained for text-to-image, so evaluate each style's editing quality.
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  The shipping iOS inpainting screen does not enable dynamic styles.
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- [Read the adapter and deployment details](https://huggingface.co/neonforestmist/Clover-Image-Tiny-Inpaint/blob/main/docs/MODEL_DETAILS.md#core-ml-and-style-mixing).
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  ## Limits and license
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@@ -123,8 +123,6 @@ Small text, hands, faces, exact logos, and very small masks can be difficult.
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  Review generated edits before sharing. The model inherits the limitations and
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  **CreativeML Open RAIL-M** obligations of Clover and Stable Diffusion 1.5 inpainting.
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- [**Technical reference, evaluation, provenance, and citation →**](https://huggingface.co/neonforestmist/Clover-Image-Tiny-Inpaint/blob/main/docs/MODEL_DETAILS.md)
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-
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  ## Evaluation and provenance
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  <details>
 
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  Inpaint HQ uses the **full Stable Diffusion 1.5 inpainting denoiser** with Clover's
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  text encoder, tokenizer, VAE, and scheduler. It is a larger model than the compact
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+ regular Clover text-to-image checkpoint. Regular Clover generates from text; Inpaint HQ requires an image and mask.
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  On the release's 24-edit held-out evaluation, HQ improved masked prompt alignment by
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  **4.8%** and reduced masked target error by **11.1%** versus the previous Clover inpainting
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  release. These are evaluation-set results; individual edits still depend on the image,
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+ mask, and prompt. [See the quality gate and selection record below](#evaluation-and-provenance).
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  ## Run an edit with Python
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  ## Styles and Apple devices
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+ The Clover iOS app linked above provides a native masking workflow.
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  Core ML resources are published [separately](https://huggingface.co/neonforestmist/Clover-Image-Tiny-Inpaint-CoreML).
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  Published Clover attention-only LoRAs are mechanically compatible in Diffusers,
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  but they were trained for text-to-image, so evaluate each style's editing quality.
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  The shipping iOS inpainting screen does not enable dynamic styles.
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+ Adapter and deployment details are included in Evaluation and provenance below.
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  ## Limits and license
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  Review generated edits before sharing. The model inherits the limitations and
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  **CreativeML Open RAIL-M** obligations of Clover and Stable Diffusion 1.5 inpainting.
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  ## Evaluation and provenance
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  <details>