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:
- 4c5b26678fb7f99937140c0c48ae43c5160d62d810f870cda539f9fdfe83bb0f
- Size of remote file:
- 6.59 MB
- SHA256:
- 509536cda0ffb96c3e238f3d4ac968d117d865a71a962a71049b99828c8d19fb
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