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Merge branch 'kx-dev' of https://github.com/kaixuanliu/diffusers into kx-dev
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docs/source/en/_toctree.yml

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title: AutoPipeline
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- local: tutorials/basic_training
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title: Train a diffusion model
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- local: tutorials/fast_diffusion
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title: Accelerate inference of text-to-image diffusion models
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title: Tutorials
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- sections:
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- local: using-diffusers/loading

docs/source/en/api/schedulers/cosine_dpm.md

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# CosineDPMSolverMultistepScheduler
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The [`CosineDPMSolverMultistepScheduler`] is a variant of [`DPMSolverMultistepScheduler`] with cosine schedule, proposed by Nichol and Dhariwal (2021).
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It is being used in the [Stable Audio Open](https://huggingface.co/papers/2407.14358) paper and the [Stability-AI/stable-audio-tool](https://github.com/Stability-AI/stable-audio-tool) codebase.
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It is being used in the [Stable Audio Open](https://huggingface.co/papers/2407.14358) paper and the [Stability-AI/stable-audio-tool](https://github.com/Stability-AI/stable-audio-tools) codebase.
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This scheduler was contributed by [Yoach Lacombe](https://huggingface.co/ylacombe).
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docs/source/en/training/lora.md

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<Tip>
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The following sections highlight parts of the training script that are important for understanding how to modify it, but it doesn't cover every aspect of the script in detail. If you're interested in learning more, feel free to read through the [script](https://github.com/huggingface/diffusers/blob/main/examples/text_to_image/text_to_image_lora.py) and let us know if you have any questions or concerns.
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The following sections highlight parts of the training script that are important for understanding how to modify it, but it doesn't cover every aspect of the script in detail. If you're interested in learning more, feel free to read through the [script](https://github.com/huggingface/diffusers/blob/main/examples/text_to_image/train_text_to_image_lora.py) and let us know if you have any questions or concerns.
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</Tip>
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docs/source/en/tutorials/fast_diffusion.md

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