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:
- b2c854994a658c44fe475fc44b8b59b70f0c890fdef01e9f77dcf4f66e0546a4
- Size of remote file:
- 6.59 MB
- SHA256:
- ce9077ed650634c3d8a29a0ef26af8ef34595725c9f72deb7273432a0b0aa656
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