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‎README.md‎

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| [Tutorial](https://huggingface.co/docs/diffusers/tutorials/tutorial_overview) | A basic crash course for learning how to use the library's most important features like using models and schedulers to build your own diffusion system, and training your own diffusion model. |
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| [Loading](https://huggingface.co/docs/diffusers/using-diffusers/loading_overview) | Guides for how to load and configure all the components (pipelines, models, and schedulers) of the library, as well as how to use different schedulers. |
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| [Pipelines for inference](https://huggingface.co/docs/diffusers/using-diffusers/pipeline_overview) | Guides for how to use pipelines for different inference tasks, batched generation, controlling generated outputs and randomness, and how to contribute a pipeline to the library. |
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| [Optimization](https://huggingface.co/docs/diffusers/optimization/opt_overview) | Guides for how to optimize your diffusion model to run faster and consume less memory. |
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| [Optimization](https://huggingface.co/docs/diffusers/optimization/fp16) | Guides for how to optimize your diffusion model to run faster and consume less memory. |
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| [Training](https://huggingface.co/docs/diffusers/training/overview) | Guides for how to train a diffusion model for different tasks with different training techniques. |
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## Contribution
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‎docs/source/en/api/pipelines/pag.md‎

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- all
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- __call__
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## StableDiffusion3PAGImg2ImgPipeline
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[[autodoc]] StableDiffusion3PAGImg2ImgPipeline
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- all
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- __call__
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## PixArtSigmaPAGPipeline
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[[autodoc]] PixArtSigmaPAGPipeline

‎examples/community/README.md‎

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‎examples/community/README_community_scripts.md‎

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| Example | Description | Code Example | Colab | Author |
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|:--------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------:|
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| Using IP-Adapter with Negative Noise | Using negative noise with IP-adapter to better control the generation (see the [original post](https://github.com/huggingface/diffusers/discussions/7167) on the forum for more details) | [IP-Adapter Negative Noise](#ip-adapter-negative-noise) | https://github.com/huggingface/notebooks/blob/main/diffusers/ip_adapter_negative_noise.ipynb | [Álvaro Somoza](https://github.com/asomoza)|
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| Asymmetric Tiling |configure seamless image tiling independently for the X and Y axes | [Asymmetric Tiling](#Asymmetric-Tiling ) |https://github.com/huggingface/notebooks/blob/main/diffusers/asymetric_tiling.ipynb | [alexisrolland](https://github.com/alexisrolland)|
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| Prompt Scheduling Callback |Allows changing prompts during a generation | [Prompt Scheduling-Callback](#Prompt-Scheduling-Callback ) |https://github.com/huggingface/notebooks/blob/main/diffusers/prompt_scheduling_callback.ipynb | [hlky](https://github.com/hlky)|
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| Using IP-Adapter with Negative Noise | Using negative noise with IP-adapter to better control the generation (see the [original post](https://github.com/huggingface/diffusers/discussions/7167) on the forum for more details) | [IP-Adapter Negative Noise](#ip-adapter-negative-noise) |[Notebook](https://github.com/huggingface/notebooks/blob/main/diffusers/ip_adapter_negative_noise.ipynb) | [Álvaro Somoza](https://github.com/asomoza)|
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| Asymmetric Tiling |configure seamless image tiling independently for the X and Y axes | [Asymmetric Tiling](#Asymmetric-Tiling ) |[Notebook](https://github.com/huggingface/notebooks/blob/main/diffusers/asymetric_tiling.ipynb) | [alexisrolland](https://github.com/alexisrolland)|
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| Prompt Scheduling Callback |Allows changing prompts during a generation | [Prompt Scheduling-Callback](#Prompt-Scheduling-Callback ) |[Notebook](https://github.com/huggingface/notebooks/blob/main/diffusers/prompt_scheduling_callback.ipynb) | [hlky](https://github.com/hlky)|
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## Example usages

‎examples/controlnet/train_controlnet.py‎

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raise ValueError("Specify either `--dataset_name` or `--train_data_dir`")
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if args.dataset_name is not None and args.train_data_dir is not None:
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raise ValueError("Specify only one of `--dataset_name` or `--train_data_dir`")
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if args.proportion_empty_prompts < 0 or args.proportion_empty_prompts > 1:
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raise ValueError("`--proportion_empty_prompts` must be in the range [0, 1].")
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data_dir=args.train_data_dir,
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)
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‎examples/controlnet/train_controlnet_sdxl.py‎

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if args.dataset_name is not None and args.train_data_dir is not None:
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raise ValueError("Specify only one of `--dataset_name` or `--train_data_dir`")
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‎examples/text_to_image/train_text_to_image_sdxl.py‎

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args.dataset_name, args.dataset_config_name, cache_dir=args.cache_dir, data_dir=args.train_data_dir
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‎src/diffusers/__init__.py‎

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"StableDiffusion3ControlNetPipeline",
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"StableDiffusion3PAGImg2ImgPipeline",
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‎src/diffusers/models/attention_processor.py‎

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‎src/diffusers/models/autoencoders/autoencoder_kl_temporal_decoder.py‎

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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import itertools
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def create_custom_forward(module):

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