theluyuan/DiffSynth-Studio
1
0
Fork 0
mirror of https://github.com/modelscope/DiffSynth-Studio.git synced 2026-03-21 08:08:13 +00:00
Code Issues Packages Projects Releases Wiki Activity

refine code & doc

Browse Source
This commit is contained in:
Artiprocher
2026-02-06 16:27:23 +08:00
parent fccb1ecdd7
commit b0bf78e915
5 changed files with 29 additions and 12 deletions
Download Patch File Download Diff File Expand all files Collapse all files

5
docs/en/Model_Details/Qwen-Image.md
View File

@@ -106,6 +106,11 @@ Special Training Scripts:
* Two-stage Split Training: [doc](/docs/en/Training/Split_Training.md), [code](/examples/qwen_image/model_training/special/split_training/)
* End-to-end Direct Distillation: [doc](/docs/en/Training/Direct_Distill.md), [code](/examples/qwen_image/model_training/lora/Qwen-Image-Distill-LoRA.sh)
DeepSpeed ZeRO Stage 3 Training: The Qwen-Image series models support DeepSpeed ZeRO Stage 3 training, which partitions the model across multiple GPUs. Taking full parameter training of the Qwen-Image model as an example, the following modifications are required:
* `--config_file examples/qwen_image/model_training/full/accelerate_config_zero3.yaml`
* `--initialize_model_on_cpu`
## Model Inference
Models are loaded via `QwenImagePipeline.from_pretrained`, see [Loading Models](/docs/en/Pipeline_Usage/Model_Inference.md#loading-models).

5
docs/en/Model_Details/Wan.md
View File

@@ -142,6 +142,11 @@ graph LR;
* Two-stage Split Training: [doc](/docs/en/Training/Split_Training.md), [code](/examples/wanvideo/model_training/special/split_training/)
* End-to-end Direct Distillation: [doc](/docs/en/Training/Direct_Distill.md), [code](/examples/wanvideo/model_training/special/direct_distill/)
DeepSpeed ZeRO Stage 3 Training: The Wan series models support DeepSpeed ZeRO Stage 3 training, which partitions the model across multiple GPUs. Taking full parameter training of the Wan2.1-T2V-14B model as an example, the following modifications are required:
* `--config_file examples/wanvideo/model_training/full/accelerate_config_zero3.yaml`
* `--initialize_model_on_cpu`
## Model Inference
Models are loaded via `WanVideoPipeline.from_pretrained`, see [Loading Models](/docs/en/Pipeline_Usage/Model_Inference.md#loading-models).

5
docs/zh/Model_Details/Qwen-Image.md
View File

@@ -106,6 +106,11 @@ graph LR;
* 两阶段拆分训练：[doc](/docs/zh/Training/Split_Training.md)、[code](/examples/qwen_image/model_training/special/split_training/)
* 端到端直接蒸馏：[doc](/docs/zh/Training/Direct_Distill.md)、[code](/examples/qwen_image/model_training/lora/Qwen-Image-Distill-LoRA.sh)
DeepSpeed ZeRO 3 训练：Qwen-Image 系列模型支持 DeepSpeed ZeRO 3 训练，将模型拆分到多个 GPU 上，以 Qwen-Image 模型的全量训练为例，需修改：
* `--config_file examples/qwen_image/model_training/full/accelerate_config_zero3.yaml`
* `--initialize_model_on_cpu`
## 模型推理
模型通过 `QwenImagePipeline.from_pretrained` 加载，详见[加载模型](/docs/zh/Pipeline_Usage/Model_Inference.md#加载模型)。

5
docs/zh/Model_Details/Wan.md
View File

@@ -143,6 +143,11 @@ graph LR;
* 两阶段拆分训练：[doc](/docs/zh/Training/Split_Training.md)、[code](/examples/wanvideo/model_training/special/split_training/)
* 端到端直接蒸馏：[doc](/docs/zh/Training/Direct_Distill.md)、[code](/examples/wanvideo/model_training/special/direct_distill/)
DeepSpeed ZeRO 3 训练：Wan 系列模型支持 DeepSpeed ZeRO 3 训练，将模型拆分到多个 GPU 上，以 Wan2.1-T2V-14B 模型的全量训练为例，需修改：
* `--config_file examples/wanvideo/model_training/full/accelerate_config_zero3.yaml`
* `--initialize_model_on_cpu`
## 模型推理
模型通过 `WanVideoPipeline.from_pretrained` 加载，详见[加载模型](/docs/zh/Pipeline_Usage/Model_Inference.md#加载模型)。