mirror of
https://github.com/modelscope/DiffSynth-Studio.git
synced 2026-04-15 06:38:20 +00:00
Support ERNIE-Image (#1389)
* ernie-image pipeline * ernie-image inference and training * style fix * ernie docs * lowvram * final style fix * pr-review * pr-fix round2 * set uniform training weight * fix * update lowvram docs
This commit is contained in:
Hong Zhang
GitHub
61
README.md
61
README.md
@@ -33,6 +33,7 @@ We believe that a well-developed open-source code framework can lower the thresh
|
||||
> DiffSynth-Studio has undergone major version updates, and some old features are no longer maintained. If you need to use old features, please switch to the [last historical version](https://github.com/modelscope/DiffSynth-Studio/tree/afd101f3452c9ecae0c87b79adfa2e22d65ffdc3) before the major version update.
|
||||
|
||||
> Currently, the development personnel of this project are limited, with most of the work handled by [Artiprocher](https://github.com/Artiprocher) and [mi804](https://github.com/mi804). Therefore, the progress of new feature development will be relatively slow, and the speed of responding to and resolving issues is limited. We apologize for this and ask developers to understand.
|
||||
|
||||
- **March 19, 2026**: Added support for [openmoss/MOVA-720p](https://modelscope.cn/models/openmoss/MOVA-720p) and [openmoss/MOVA-360p](https://modelscope.cn/models/openmoss/MOVA-360p) models, including training and inference capabilities. [Documentation](/docs/en/Model_Details/Wan.md) and [example code](/examples/mova/) are now available.
|
||||
|
||||
- **March 12, 2026**: We have added support for the [LTX-2.3](https://modelscope.cn/models/Lightricks/LTX-2.3) audio-video generation model. The features includes text-to-audio/video, image-to-audio/video, IC-LoRA control, audio-to-video, and audio-video inpainting. We have supported the complete inference and training functionalities. For details, please refer to the [documentation](/docs/en/Model_Details/LTX-2.md) and [code](/examples/ltx2/).
|
||||
@@ -876,6 +877,66 @@ Example code for Wan is available at: [/examples/wanvideo/](/examples/wanvideo/)
|
||||
|
||||
</details>
|
||||
|
||||
#### ERNIE-Image: [/docs/en/Model_Details/ERNIE-Image.md](/docs/en/Model_Details/ERNIE-Image.md)
|
||||
|
||||
<details>
|
||||
|
||||
<summary>Quick Start</summary>
|
||||
|
||||
Running the following code will quickly load the [baidu/ERNIE-Image](https://www.modelscope.cn/models/baidu/ERNIE-Image) model and perform inference. VRAM management is enabled, and the framework will automatically control the loading of model parameters based on available VRAM. The model can run with a minimum of 3GB VRAM.
|
||||
|
||||
```python
|
||||
from diffsynth.pipelines.ernie_image import ErnieImagePipeline, ModelConfig
|
||||
import torch
|
||||
|
||||
vram_config = {
|
||||
"offload_dtype": torch.bfloat16,
|
||||
"offload_device": "cpu",
|
||||
"onload_dtype": torch.bfloat16,
|
||||
"onload_device": "cpu",
|
||||
"preparing_dtype": torch.bfloat16,
|
||||
"preparing_device": "cuda",
|
||||
"computation_dtype": torch.bfloat16,
|
||||
"computation_device": "cuda",
|
||||
}
|
||||
pipe = ErnieImagePipeline.from_pretrained(
|
||||
torch_dtype=torch.bfloat16,
|
||||
device='cuda',
|
||||
model_configs=[
|
||||
ModelConfig(model_id="baidu/ERNIE-Image", origin_file_pattern="transformer/diffusion_pytorch_model*.safetensors", **vram_config),
|
||||
ModelConfig(model_id="baidu/ERNIE-Image", origin_file_pattern="text_encoder/model.safetensors", **vram_config),
|
||||
ModelConfig(model_id="baidu/ERNIE-Image", origin_file_pattern="vae/diffusion_pytorch_model.safetensors", **vram_config),
|
||||
],
|
||||
tokenizer_config=ModelConfig(model_id="baidu/ERNIE-Image", origin_file_pattern="tokenizer/"),
|
||||
vram_limit=torch.cuda.mem_get_info("cuda")[1] / (1024 ** 3) - 0.5,
|
||||
)
|
||||
|
||||
image = pipe(
|
||||
prompt="一只黑白相间的中华田园犬",
|
||||
negative_prompt="",
|
||||
height=1024,
|
||||
width=1024,
|
||||
seed=42,
|
||||
num_inference_steps=50,
|
||||
cfg_scale=4.0,
|
||||
)
|
||||
image.save("output.jpg")
|
||||
```
|
||||
|
||||
</details>
|
||||
|
||||
<details>
|
||||
|
||||
<summary>Examples</summary>
|
||||
|
||||
Example code for ERNIE-Image is available at: [/examples/ernie_image/](/examples/ernie_image/)
|
||||
|
||||
| Model ID | Inference | Low VRAM Inference | Full Training | Full Training Validation | LoRA Training | LoRA Training Validation |
|
||||
|-|-|-|-|-|-|-|
|
||||
|[baidu/ERNIE-Image: T2I](https://www.modelscope.cn/models/baidu/ERNIE-Image)|[code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/ernie_image/model_inference/Ernie-Image-T2I.py)|[code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/ernie_image/model_inference_low_vram/Ernie-Image-T2I.py)|[code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/ernie_image/model_training/full/Ernie-Image-T2I.sh)|[code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/ernie_image/model_training/validate_full/Ernie-Image-T2I.py)|[code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/ernie_image/model_training/lora/Ernie-Image-T2I.sh)|[code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/ernie_image/model_training/validate_lora/Ernie-Image-T2I.py)|
|
||||
|
||||
</details>
|
||||
|
||||
## Innovative Achievements
|
||||
|
||||
DiffSynth-Studio is not just an engineered model framework, but also an incubator for innovative achievements.
|
||||
|
||||
Reference in New Issue
Block a user