#
Diffusers

🤗 Diffusers는 이미지, 오디오, 심지어 분자의 3D 구조를 생성하기 위한 최첨단 사전 훈련된 diffusion 모델을 위한 라이브러리입니다. 간단한 추론 솔루션을 찾고 있든, 자체 diffusion 모델을 훈련하고 싶든, 🤗 Diffusers는 두 가지 모두를 지원하는 모듈식 툴박스입니다. 저희 라이브러리는 성능보다 사용성, 간편함보다 단순함, 그리고 추상화보다 사용자 지정 가능성에 중점을 두고 설계되었습니다.

이 라이브러리에는 세 가지 주요 구성 요소가 있습니다:

- 몇 줄의 코드만으로 추론할 수 있는 최첨단 diffusion 파이프라인.
- 생성 속도와 품질 간의 균형을 맞추기 위해 상호교환적으로 사용할 수 있는 노이즈 스케줄러.
- 빌딩 블록으로 사용할 수 있고 스케줄러와 결합하여 자체적인 end-to-end diffusion 시스템을 만들 수 있는 사전 학습된 모델.

Tutorials

결과물을 생성하고, 나만의 diffusion 시스템을 구축하고, 확산 모델을 훈련하는 데 필요한 기본 기술을 배워보세요. 🤗 Diffusers를 처음 사용하는 경우 여기에서 시작하는 것이 좋습니다!

How-to guides

파이프라인, 모델, 스케줄러를 로드하는 데 도움이 되는 실용적인 가이드입니다. 또한 특정 작업에 파이프라인을 사용하고, 출력 생성 방식을 제어하고, 추론 속도에 맞게 최적화하고, 다양한 학습 기법을 사용하는 방법도 배울 수 있습니다.

Conceptual guides

라이브러리가 왜 이런 방식으로 설계되었는지 이해하고, 라이브러리 이용에 대한 윤리적 가이드라인과 안전 구현에 대해 자세히 알아보세요.

Reference

🤗 Diffusers 클래스 및 메서드의 작동 방식에 대한 기술 설명.

##
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_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