Instructions to use Langboat/Guohua-Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Langboat/Guohua-Diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Langboat/Guohua-Diffusion", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
| license: creativeml-openrail-m | |
| tags: | |
| - stable-diffusion | |
| - text-to-image | |
| # Guohua Diffusion | |
| This is the fine-tuned Stable Diffusion model trained on traditional Chinese paintings. | |
| Use **guohua style** in your prompts for the effect. | |
| ## Sample Image | |
|  | |
|  | |
| ## How to use | |
| #### WebUI | |
| Download the `guohua.ckpt` in model files. | |
| #### Diffusers | |
| This model can be used just like any other Stable Diffusion model. For more information, | |
| please have a look at the [Stable Diffusion](https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion). | |
| ```python | |
| #!pip install diffusers transformers scipy torch | |
| from diffusers import StableDiffusionPipeline | |
| import torch | |
| model_id = "Langboat/Guohua-Diffusion" | |
| pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16) | |
| pipe = pipe.to("cuda") | |
| prompt = "The Godfather poster in guohua style" | |
| image = pipe(prompt).images[0] | |
| image.save("./the_god_father.png") | |
| ``` | |