theluyuan/DiffSynth-Studio
1
0
Fork 0
mirror of https://github.com/modelscope/DiffSynth-Studio.git synced 2026-03-20 23:58:12 +00:00
Code Issues Packages Projects Releases Wiki Activity

Add files via upload

Browse Source 
第一版翻译完成，保留了getStart目录，有一些名词还是需要重新检查
This commit is contained in:
yrk111222
2024-10-18 18:02:52 +08:00
committed by GitHub
parent 24b78148b8
commit 883d26abb4
15 changed files with 308 additions and 38 deletions
Download Patch File Download Diff File Expand all files Collapse all files

1
docs/source_en/GetStarted/Models.md
View File

@@ -2,6 +2,7 @@
Until now, DiffSynth Studio has supported the following models:
* [CogVideoX](https://huggingface.co/THUDM/CogVideoX-5b)
* [FLUX](https://huggingface.co/black-forest-labs/FLUX.1-dev)
* [ExVideo](https://huggingface.co/ECNU-CILab/ExVideo-SVD-128f-v1)
* [Kolors](https://huggingface.co/Kwai-Kolors/Kolors)

15
docs/source_en/GetStarted/Pipelines.md
View File

@@ -1,27 +1,22 @@
# Pipelines
So far, the following table lists our pipelines and the models supported by each pipeline.
DiffSynth-Studio includes multiple pipelines, categorized into two types: image generation and video generation.
## Image Pipelines
Pipelines for generating images from text descriptions. Each pipeline relies on specific encoder and decoder models.
| Pipeline | Models |
|----------------------------|----------------------------------------------------------------|
| HunyuanDiTImagePipeline | text_encoder: HunyuanDiTCLIPTextEncoder<br>text_encoder_t5: HunyuanDiTT5TextEncoder<br>dit: HunyuanDiT<br>vae_decoder: SDVAEDecoder<br>vae_encoder: SDVAEEncoder |
| SDImagePipeline | text_encoder: SDTextEncoder<br>unet: SDUNet<br>vae_decoder: SDVAEDecoder<br>vae_encoder: SDVAEEncoder<br>controlnet: MultiControlNetManager<br>ipadapter_image_encoder: IpAdapterCLIPImageEmbedder<br>ipadapter: SDIpAdapter |
| SD3ImagePipeline | text_encoder_1: SD3TextEncoder1<br>text_encoder_2: SD3TextEncoder2<br>text_encoder_3: SD3TextEncoder3<br>dit: SD3DiT<br>vae_decoder: SD3VAEDecoder<br>vae_encoder: SD3VAEEncoder |
| SDXLImagePipeline | text_encoder: SDXLTextEncoder<br>text_encoder_2: SDXLTextEncoder2<br>text_encoder_kolors: ChatGLMModel<br>unet: SDXLUNet<br>vae_decoder: SDXLVAEDecoder<br>vae_encoder: SDXLVAEEncoder<br>controlnet: MultiControlNetManager<br>ipadapter_image_encoder: IpAdapterXLCLIPImageEmbedder<br>ipadapter: SDXLIpAdapter |
| SD3ImagePipeline | text_encoder_1: SD3TextEncoder1<br>text_encoder_2: SD3TextEncoder2<br>text_encoder_3: SD3TextEncoder3<br>dit: SD3DiT<br>vae_decoder: SD3VAEDecoder<br>vae_encoder: SD3VAEEncoder |
| HunyuanDiTImagePipeline | text_encoder: HunyuanDiTCLIPTextEncoder<br>text_encoder_t5: HunyuanDiTT5TextEncoder<br>dit: HunyuanDiT<br>vae_decoder: SDVAEDecoder<br>vae_encoder: SDVAEEncoder |
| FluxImagePipeline | text_encoder_1: FluxTextEncoder1<br>text_encoder_2: FluxTextEncoder2<br>dit: FluxDiT<br>vae_decoder: FluxVAEDecoder<br>vae_encoder: FluxVAEEncoder |
## Video Pipelines
Pipelines for generating videos from text descriptions. In addition to the models required for image generation, they include models for handling motion modules.
| Pipeline | Models |
|----------------------------|----------------------------------------------------------------|
| SDVideoPipeline | text_encoder: SDTextEncoder<br>unet: SDUNet<br>vae_decoder: SDVAEDecoder<br>vae_encoder: SDVAEEncoder<br>controlnet: MultiControlNetManager<br>ipadapter_image_encoder: IpAdapterCLIPImageEmbedder<br>ipadapter: SDIpAdapter<br>motion_modules: SDMotionModel |
| SDXLVideoPipeline | text_encoder: SDXLTextEncoder<br>text_encoder_2: SDXLTextEncoder2<br>text_encoder_kolors: ChatGLMModel<br>unet: SDXLUNet<br>vae_decoder: SDXLVAEDecoder<br>vae_encoder: SDXLVAEEncoder<br>ipadapter_image_encoder: IpAdapterXLCLIPImageEmbedder<br>ipadapter: SDXLIpAdapter<br>motion_modules: SDXLMotionModel |
| SVDVideoPipeline | image_encoder: SVDImageEncoder<br>unet: SVDUNet<br>vae_encoder: SVDVAEEncoder<br>vae_decoder: SVDVAEDecoder |
| CogVideoPipeline | text_encoder: FluxTextEncoder2<br>dit: CogDiT<br>vae_encoder: CogVAEEncoder<br>vae_decoder: CogVAEDecoder |

4
docs/source_en/GetStarted/Schedulers.md
View File

@@ -1,11 +1,11 @@
# Schedulers
Schedulers control the entire denoising (or sampling) process of the model. When loading the Pipeline, DiffSynth automatically selects the most suitable schedulers for the current Pipeline, requiring no additional configuration.
Schedulers control the entire denoising (or sampling) process of the model. When loading the Pipeline, DiffSynth automatically selects the most suitable schedulers for the current Pipeline, **requiring no additional configuration**.
The supported schedulers are:
- **EnhancedDDIMScheduler**: Extends the denoising process introduced in the Denoising Diffusion Probabilistic Models (DDPM) with non-Markovian guidance.
- **FlowMatchScheduler**: Implements the flow matching sampling method introduced in Stable Diffusion 3.
- **FlowMatchScheduler**: Implements the flow matching sampling method introduced in [Stable Diffusion 3](https://arxiv.org/abs/2403.03206).
- **ContinuousODEScheduler**: A scheduler based on Ordinary Differential Equations (ODE).