Instructions to use Amyww/2000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Amyww/2000 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Datou1111/shou_xin", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Amyww/2000") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
| tags: | |
| - text-to-image | |
| - lora | |
| - diffusers | |
| - template:diffusion-lora | |
| widget: | |
| - text: '-' | |
| output: | |
| url: images/微信图片_20241205121147.png | |
| base_model: Datou1111/shou_xin | |
| instance_prompt: null | |
| license: bigscience-bloom-rail-1.0 | |
| # yyy | |
| <Gallery /> | |
| ## Download model | |
| [Download](/Amyww/2000/tree/main) them in the Files & versions tab. | |