Instructions to use wujia/fantuan_result with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wujia/fantuan_result with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("wujia/fantuan_result") prompt = "a photo of fantuan portrait" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 2b057fec3e87b58b05bb1ee49dbdb418ac6aa11e2990f9e725bbff3dd8520d94
- Size of remote file:
- 3.29 MB
- SHA256:
- a09b5720362a6b5c6da0afd96a5fb48cc1d0e2d5b15b5419e311832ea8956cbf
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