diff --git a/docs/source/en/_toctree.yml b/docs/source/en/_toctree.yml index 87adafad5b7c..b095b2cc1a73 100644 --- a/docs/source/en/_toctree.yml +++ b/docs/source/en/_toctree.yml @@ -1,36 +1,39 @@ -- sections: +- title: Get started + sections: - local: index - title: 🧨 Diffusers + title: Diffusers + - local: installation + title: Installation - local: quicktour title: Quicktour - local: stable_diffusion title: Effective and efficient diffusion - - local: installation - title: Installation - title: Get started -- sections: - - local: tutorials/tutorial_overview - title: Overview - - local: using-diffusers/write_own_pipeline - title: Understanding pipelines, models and schedulers - - local: tutorials/autopipeline - title: AutoPipeline - - local: tutorials/basic_training - title: Train a diffusion model - title: Tutorials -- sections: + +- title: DiffusionPipeline + isExpanded: false + sections: - local: using-diffusers/loading title: Load pipelines + - local: tutorials/autopipeline + title: AutoPipeline - local: using-diffusers/custom_pipeline_overview title: Load community pipelines and components + - local: using-diffusers/callback + title: Pipeline callbacks + - local: using-diffusers/reusing_seeds + title: Reproducible pipelines - local: using-diffusers/schedulers title: Load schedulers and models + - local: using-diffusers/scheduler_features + title: Scheduler features - local: using-diffusers/other-formats title: Model files and layouts - local: using-diffusers/push_to_hub title: Push files to the Hub - title: Load pipelines and adapters -- sections: + +- title: Adapters + isExpanded: false + sections: - local: tutorials/using_peft_for_inference title: LoRA - local: using-diffusers/ip_adapter @@ -43,25 +46,12 @@ title: DreamBooth - local: using-diffusers/textual_inversion_inference title: Textual inversion - title: Adapters + +- title: Inference isExpanded: false -- sections: - - local: using-diffusers/unconditional_image_generation - title: Unconditional image generation - - local: using-diffusers/conditional_image_generation - title: Text-to-image - - local: using-diffusers/img2img - title: Image-to-image - - local: using-diffusers/inpaint - title: Inpainting - - local: using-diffusers/text-img2vid - title: Video generation - - local: using-diffusers/depth2img - title: Depth-to-image - title: Generative tasks -- sections: - - local: using-diffusers/overview_techniques - title: Overview + sections: + - local: using-diffusers/weighted_prompts + title: Prompt techniques - local: using-diffusers/create_a_server title: Create a server - local: using-diffusers/batched_inference @@ -76,14 +66,38 @@ title: Reproducible pipelines - local: using-diffusers/image_quality title: Controlling image quality - - local: using-diffusers/weighted_prompts - title: Prompt techniques - title: Inference techniques -- sections: - - local: advanced_inference/outpaint - title: Outpainting - title: Advanced inference -- sections: + +- title: Inference optimization + isExpanded: false + sections: + - local: optimization/fp16 + title: Accelerate inference + - local: optimization/cache + title: Caching + - local: optimization/memory + title: Reduce memory usage + - local: optimization/speed-memory-optims + title: Compile and offloading quantized models + - title: Community optimizations + sections: + - local: optimization/pruna + title: Pruna + - local: optimization/xformers + title: xFormers + - local: optimization/tome + title: Token merging + - local: optimization/deepcache + title: DeepCache + - local: optimization/tgate + title: TGATE + - local: optimization/xdit + title: xDiT + - local: optimization/para_attn + title: ParaAttention + +- title: Hybrid Inference + isExpanded: false + sections: - local: hybrid_inference/overview title: Overview - local: hybrid_inference/vae_decode @@ -92,8 +106,10 @@ title: VAE Encode - local: hybrid_inference/api_reference title: API Reference - title: Hybrid Inference -- sections: + +- title: Modular Diffusers + isExpanded: false + sections: - local: modular_diffusers/overview title: Overview - local: modular_diffusers/modular_pipeline @@ -112,41 +128,19 @@ title: Auto Pipeline Blocks - local: modular_diffusers/end_to_end_guide title: End-to-End Example - title: Modular Diffusers -- sections: - - local: using-diffusers/consisid - title: ConsisID - - local: using-diffusers/sdxl - title: Stable Diffusion XL - - local: using-diffusers/sdxl_turbo - title: SDXL Turbo - - local: using-diffusers/kandinsky - title: Kandinsky - - local: using-diffusers/omnigen - title: OmniGen - - local: using-diffusers/pag - title: PAG - - local: using-diffusers/inference_with_lcm - title: Latent Consistency Model - - local: using-diffusers/shap-e - title: Shap-E - - local: using-diffusers/diffedit - title: DiffEdit - - local: using-diffusers/inference_with_tcd_lora - title: Trajectory Consistency Distillation-LoRA - - local: using-diffusers/svd - title: Stable Video Diffusion - - local: using-diffusers/marigold_usage - title: Marigold Computer Vision - title: Specific pipeline examples -- sections: + +- title: Training + isExpanded: false + sections: - local: training/overview title: Overview - local: training/create_dataset title: Create a dataset for training - local: training/adapt_a_model title: Adapt a model to a new task - - isExpanded: false + - local: tutorials/basic_training + title: Train a diffusion model + - title: Models sections: - local: training/unconditional_training title: Unconditional image generation @@ -166,8 +160,7 @@ title: InstructPix2Pix - local: training/cogvideox title: CogVideoX - title: Models - - isExpanded: false + - title: Methods sections: - local: training/text_inversion title: Textual Inversion @@ -181,9 +174,10 @@ title: Latent Consistency Distillation - local: training/ddpo title: Reinforcement learning training with DDPO - title: Methods - title: Training -- sections: + +- title: Quantization + isExpanded: false + sections: - local: quantization/overview title: Getting Started - local: quantization/bitsandbytes @@ -194,50 +188,76 @@ title: torchao - local: quantization/quanto title: quanto - title: Quantization Methods -- sections: - - local: optimization/fp16 - title: Accelerate inference - - local: optimization/cache - title: Caching - - local: optimization/memory - title: Reduce memory usage - - local: optimization/speed-memory-optims - title: Compile and offloading quantized models - - local: optimization/pruna - title: Pruna - - local: optimization/xformers - title: xFormers - - local: optimization/tome - title: Token merging - - local: optimization/deepcache - title: DeepCache - - local: optimization/tgate - title: TGATE - - local: optimization/xdit - title: xDiT - - local: optimization/para_attn - title: ParaAttention - - sections: - - local: using-diffusers/stable_diffusion_jax_how_to - title: JAX/Flax - - local: optimization/onnx - title: ONNX - - local: optimization/open_vino - title: OpenVINO - - local: optimization/coreml - title: Core ML - title: Optimized model formats - - sections: - - local: optimization/mps - title: Metal Performance Shaders (MPS) - - local: optimization/habana - title: Intel Gaudi - - local: optimization/neuron - title: AWS Neuron - title: Optimized hardware - title: Accelerate inference and reduce memory -- sections: + +- title: Model accelerators and hardware + isExpanded: false + sections: + - local: using-diffusers/stable_diffusion_jax_how_to + title: JAX/Flax + - local: optimization/onnx + title: ONNX + - local: optimization/open_vino + title: OpenVINO + - local: optimization/coreml + title: Core ML + - local: optimization/mps + title: Metal Performance Shaders (MPS) + - local: optimization/habana + title: Intel Gaudi + - local: optimization/neuron + title: AWS Neuron + +- title: Specific pipeline examples + isExpanded: false + sections: + - local: using-diffusers/consisid + title: ConsisID + - local: using-diffusers/sdxl + title: Stable Diffusion XL + - local: using-diffusers/sdxl_turbo + title: SDXL Turbo + - local: using-diffusers/kandinsky + title: Kandinsky + - local: using-diffusers/omnigen + title: OmniGen + - local: using-diffusers/pag + title: PAG + - local: using-diffusers/inference_with_lcm + title: Latent Consistency Model + - local: using-diffusers/shap-e + title: Shap-E + - local: using-diffusers/diffedit + title: DiffEdit + - local: using-diffusers/inference_with_tcd_lora + title: Trajectory Consistency Distillation-LoRA + - local: using-diffusers/svd + title: Stable Video Diffusion + - local: using-diffusers/marigold_usage + title: Marigold Computer Vision + +- title: Resources + isExpanded: false + sections: + - title: Task recipes + sections: + - local: using-diffusers/unconditional_image_generation + title: Unconditional image generation + - local: using-diffusers/conditional_image_generation + title: Text-to-image + - local: using-diffusers/img2img + title: Image-to-image + - local: using-diffusers/inpaint + title: Inpainting + - local: advanced_inference/outpaint + title: Outpainting + - local: using-diffusers/text-img2vid + title: Video generation + - local: using-diffusers/depth2img + title: Depth-to-image + - local: using-diffusers/write_own_pipeline + title: Understanding pipelines, models and schedulers + - local: community_projects + title: Projects built with Diffusers - local: conceptual/philosophy title: Philosophy - local: using-diffusers/controlling_generation @@ -248,13 +268,11 @@ title: Diffusers' Ethical Guidelines - local: conceptual/evaluation title: Evaluating Diffusion Models - title: Conceptual Guides -- sections: - - local: community_projects - title: Projects built with Diffusers - title: Community Projects -- sections: - - isExpanded: false + +- title: API + isExpanded: false + sections: + - title: Main Classes sections: - local: api/configuration title: Configuration @@ -264,8 +282,7 @@ title: Outputs - local: api/quantization title: Quantization - title: Main Classes - - isExpanded: false + - title: Loaders sections: - local: api/loaders/ip_adapter title: IP-Adapter @@ -281,14 +298,14 @@ title: SD3Transformer2D - local: api/loaders/peft title: PEFT - title: Loaders - - isExpanded: false + - title: Models sections: - local: api/models/overview title: Overview - local: api/models/auto_model title: AutoModel - - sections: + - title: ControlNets + sections: - local: api/models/controlnet title: ControlNetModel - local: api/models/controlnet_union @@ -303,8 +320,8 @@ title: SD3ControlNetModel - local: api/models/controlnet_sparsectrl title: SparseControlNetModel - title: ControlNets - - sections: + - title: Transformers + sections: - local: api/models/allegro_transformer3d title: AllegroTransformer3DModel - local: api/models/aura_flow_transformer2d @@ -363,8 +380,8 @@ title: TransformerTemporalModel - local: api/models/wan_transformer_3d title: WanTransformer3DModel - title: Transformers - - sections: + - title: UNets + sections: - local: api/models/stable_cascade_unet title: StableCascadeUNet - local: api/models/unet @@ -379,8 +396,8 @@ title: UNetMotionModel - local: api/models/uvit2d title: UViT2DModel - title: UNets - - sections: + - title: VAEs + sections: - local: api/models/asymmetricautoencoderkl title: AsymmetricAutoencoderKL - local: api/models/autoencoder_dc @@ -411,9 +428,7 @@ title: Tiny AutoEncoder - local: api/models/vq title: VQModel - title: VAEs - title: Models - - isExpanded: false + - title: Pipelines sections: - local: api/pipelines/overview title: Overview @@ -555,7 +570,8 @@ title: Stable Audio - local: api/pipelines/stable_cascade title: Stable Cascade - - sections: + - title: Stable Diffusion + sections: - local: api/pipelines/stable_diffusion/overview title: Overview - local: api/pipelines/stable_diffusion/depth2img @@ -592,7 +608,6 @@ title: T2I-Adapter - local: api/pipelines/stable_diffusion/text2img title: Text-to-image - title: Stable Diffusion - local: api/pipelines/stable_unclip title: Stable unCLIP - local: api/pipelines/text_to_video @@ -611,8 +626,7 @@ title: Wan - local: api/pipelines/wuerstchen title: Wuerstchen - title: Pipelines - - isExpanded: false + - title: Schedulers sections: - local: api/schedulers/overview title: Overview @@ -682,8 +696,7 @@ title: UniPCMultistepScheduler - local: api/schedulers/vq_diffusion title: VQDiffusionScheduler - title: Schedulers - - isExpanded: false + - title: Internal classes sections: - local: api/internal_classes_overview title: Overview @@ -701,5 +714,3 @@ title: VAE Image Processor - local: api/video_processor title: Video Processor - title: Internal classes - title: API diff --git a/docs/source/en/tutorials/tutorial_overview.md b/docs/source/en/tutorials/tutorial_overview.md deleted file mode 100644 index e8700d82c0c1..000000000000 --- a/docs/source/en/tutorials/tutorial_overview.md +++ /dev/null @@ -1,23 +0,0 @@ - - -# Overview - -Welcome to 🧨 Diffusers! If you're new to diffusion models and generative AI, and want to learn more, then you've come to the right place. These beginner-friendly tutorials are designed to provide a gentle introduction to diffusion models and help you understand the library fundamentals - the core components and how 🧨 Diffusers is meant to be used. - -You'll learn how to use a pipeline for inference to rapidly generate things, and then deconstruct that pipeline to really understand how to use the library as a modular toolbox for building your own diffusion systems. In the next lesson, you'll learn how to train your own diffusion model to generate what you want. - -After completing the tutorials, you'll have gained the necessary skills to start exploring the library on your own and see how to use it for your own projects and applications. - -Feel free to join our community on [Discord](https://discord.com/invite/JfAtkvEtRb) or the [forums](https://discuss.huggingface.co/c/discussion-related-to-httpsgithubcomhuggingfacediffusers/63) to connect and collaborate with other users and developers! - -Let's start diffusing! 🧨 diff --git a/docs/source/en/using-diffusers/overview_techniques.md b/docs/source/en/using-diffusers/overview_techniques.md deleted file mode 100644 index a0b37cc52fef..000000000000 --- a/docs/source/en/using-diffusers/overview_techniques.md +++ /dev/null @@ -1,18 +0,0 @@ - - -# Overview - -The inference pipeline supports and enables a wide range of techniques that are divided into two categories: - -* Pipeline functionality: these techniques modify the pipeline or extend it for other applications. For example, pipeline callbacks add new features to a pipeline and a pipeline can also be extended for distributed inference. -* Improve inference quality: these techniques increase the visual quality of the generated images. For example, you can enhance your prompts with GPT2 to create better images with lower effort.