Instructions to use armhebb/fal_pattern with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use armhebb/fal_pattern with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("undefined", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("armhebb/fal_pattern") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- b57a9e25f97e4de0d49542c03187c299d7bba8e3dd6f0f7b745efa9890cf5c7d
- Size of remote file:
- 307 MB
- SHA256:
- adba0c38a5afae741a30ccb9fd049b99749e78df9cc6e1065ce50a84bc5587b2
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