[docs] Update toctree (#11936)

* update

* fix

* feedback

---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

docs/source/en/_toctree.yml

-- 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
@@ -194,31 +188,10 @@
     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:
+
+- title: Model accelerators and hardware
+  isExpanded: false
+  sections:
   - local: using-diffusers/stable_diffusion_jax_how_to
     title: JAX/Flax
   - local: optimization/onnx
@@ -227,17 +200,64 @@
     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: 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

docs/source/en/tutorials/tutorial_overview.md

-<!--Copyright 2025 The HuggingFace Team. All rights reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
-the License. You may obtain a copy of the License at
-
-http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
-an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
-specific language governing permissions and limitations under the License.
--->
-
-# 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! 🧨

docs/source/en/using-diffusers/overview_techniques.md

-<!--Copyright 2025 The HuggingFace Team. All rights reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
-the License. You may obtain a copy of the License at
-
-http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
-an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
-specific language governing permissions and limitations under the License.
--->
-
-# 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.