Instructions to use iskandre/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use iskandre/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("iskandre/output") prompt = "a photo of cat" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- b50c8fb1550d26c9ed98a0122feab83516d23878f0acb77ec625bf649dc47cbe
- Size of remote file:
- 6.59 MB
- SHA256:
- 3c4c4dc51e7811c18f70531260bad7c884643d1a77bc2abccf9afdc2284b2252
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