Instructions to use wangjun/brav5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wangjun/brav5 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wangjun/brav5", torch_dtype=torch.bfloat16, device_map="cuda") 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:
- 06853bb58338f8f68bf4bdd15cdca301cb5a5636a4068d6172d364d2f71ee081
- Size of remote file:
- 492 MB
- SHA256:
- 0d26aa1ea54bcb12e5d058240b0384081afc342e4dcf79a5db6a251fd5fd9cd3
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