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
- Draw Things
- DiffusionBee
- Xet hash:
- 007ca326ab34bc483878fa13fb7e2f69655677cbdffd56c010c9dba7e059d702
- Size of remote file:
- 6.59 MB
- SHA256:
- 842f47b501dfebd2aa144f804ccb5c3500efa8ee38af2b2d9ac45a6bf91a53b6
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