Diffusers documentation

Diffusers

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Diffusers

🤗 Diffusers is the go-to library for state-of-the-art pretrained diffusion models for generating images, audio, and even 3D structures of molecules. Whether you’re looking for a simple inference solution or want to train your own diffusion model, 🤗 Diffusers is a modular toolbox that supports both. Our library is designed with a focus on usability over performance, simple over easy, and customizability over abstractions.

The library has three main components:

  • State-of-the-art diffusion pipelines for inference with just a few lines of code.
  • Interchangeable noise schedulers for balancing trade-offs between generation speed and quality.
  • Pretrained models that can be used as building blocks, and combined with schedulers, for creating your own end-to-end diffusion systems.

Supported pipelines

Pipeline Paper/Repository Tasks
alt_diffusion AltCLIP: Altering the Language Encoder in CLIP for Extended Language Capabilities Image-to-Image Text-Guided Generation
audio_diffusion Audio Diffusion Unconditional Audio Generation
controlnet Adding Conditional Control to Text-to-Image Diffusion Models Image-to-Image Text-Guided Generation
cycle_diffusion Unifying Diffusion Models’ Latent Space, with Applications to CycleDiffusion and Guidance Image-to-Image Text-Guided Generation
dance_diffusion Dance Diffusion Unconditional Audio Generation
ddpm Denoising Diffusion Probabilistic Models Unconditional Image Generation
ddim Denoising Diffusion Implicit Models Unconditional Image Generation
if IF Image Generation
if_img2img IF Image-to-Image Generation
if_inpainting IF Image-to-Image Generation
latent_diffusion High-Resolution Image Synthesis with Latent Diffusion Models Text-to-Image Generation
latent_diffusion High-Resolution Image Synthesis with Latent Diffusion Models Super Resolution Image-to-Image
latent_diffusion_uncond High-Resolution Image Synthesis with Latent Diffusion Models Unconditional Image Generation
paint_by_example Paint by Example: Exemplar-based Image Editing with Diffusion Models Image-Guided Image Inpainting
pndm Pseudo Numerical Methods for Diffusion Models on Manifolds Unconditional Image Generation
score_sde_ve Score-Based Generative Modeling through Stochastic Differential Equations Unconditional Image Generation
score_sde_vp Score-Based Generative Modeling through Stochastic Differential Equations Unconditional Image Generation
semantic_stable_diffusion Semantic Guidance Text-Guided Generation
stable_diffusion_adapter T2I-Adapter Image-to-Image Text-Guided Generation
stable_diffusion_text2img Stable Diffusion Text-to-Image Generation
stable_diffusion_img2img Stable Diffusion Image-to-Image Text-Guided Generation
stable_diffusion_inpaint Stable Diffusion Text-Guided Image Inpainting
stable_diffusion_panorama MultiDiffusion Text-to-Panorama Generation
stable_diffusion_pix2pix InstructPix2Pix: Learning to Follow Image Editing Instructions Text-Guided Image Editing
stable_diffusion_pix2pix_zero Zero-shot Image-to-Image Translation Text-Guided Image Editing
stable_diffusion_attend_and_excite Attend-and-Excite: Attention-Based Semantic Guidance for Text-to-Image Diffusion Models Text-to-Image Generation
stable_diffusion_self_attention_guidance Improving Sample Quality of Diffusion Models Using Self-Attention Guidance Text-to-Image Generation Unconditional Image Generation
stable_diffusion_image_variation Stable Diffusion Image Variations Image-to-Image Generation
stable_diffusion_latent_upscale Stable Diffusion Latent Upscaler Text-Guided Super Resolution Image-to-Image
stable_diffusion_model_editing Editing Implicit Assumptions in Text-to-Image Diffusion Models Text-to-Image Model Editing
stable_diffusion_2 Stable Diffusion 2 Text-to-Image Generation
stable_diffusion_2 Stable Diffusion 2 Text-Guided Image Inpainting
stable_diffusion_2 Depth-Conditional Stable Diffusion Depth-to-Image Generation
stable_diffusion_2 Stable Diffusion 2 Text-Guided Super Resolution Image-to-Image
stable_diffusion_safe Safe Stable Diffusion Text-Guided Generation
stable_unclip Stable unCLIP Text-to-Image Generation
stable_unclip Stable unCLIP Image-to-Image Text-Guided Generation
stochastic_karras_ve Elucidating the Design Space of Diffusion-Based Generative Models Unconditional Image Generation
text_to_video_sd Modelscope’s Text-to-video-synthesis Model in Open Domain Text-to-Video Generation
unclip Hierarchical Text-Conditional Image Generation with CLIP Latents(implementation by kakaobrain) Text-to-Image Generation
versatile_diffusion Versatile Diffusion: Text, Images and Variations All in One Diffusion Model Text-to-Image Generation
versatile_diffusion Versatile Diffusion: Text, Images and Variations All in One Diffusion Model Image Variations Generation
versatile_diffusion Versatile Diffusion: Text, Images and Variations All in One Diffusion Model Dual Image and Text Guided Generation
vq_diffusion Vector Quantized Diffusion Model for Text-to-Image Synthesis Text-to-Image Generation
stable_diffusion_ldm3d LDM3D: Latent Diffusion Model for 3D Text to Image and Depth Generation