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
- Draw Things
- DiffusionBee
- Xet hash:
- 6f77f6093391c03e57fd2bc607a2c8f5ad5c09d9625eebc4d75471fad06ad8d5
- Size of remote file:
- 6.59 MB
- SHA256:
- 55b006e9089f26a49a6fac8dd1fc449c4bb7c1e9ee7657d9e7f4de3f0e707b05
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