Instructions to use Chenhsing/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Chenhsing/output 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("Chenhsing/output") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 7c30aec610ed0e315ee7d8ec6c22e61c30b096a65a4fe237d73cfafe75bd2478
- Size of remote file:
- 3.29 MB
- SHA256:
- a7542a9f74cc9ea7b03db38da83c1d3d9ee310ad6b9703bbf36b24e19ecceba6
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