Instructions to use humflywol/bl_diffuser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use humflywol/bl_diffuser with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("humflywol/bl_diffuser", 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
- Draw Things
- DiffusionBee
- Xet hash:
- 6567b1e5bfae46206ab6fc429bd35165c891b03012047ceb639599a9c4cec0ac
- Size of remote file:
- 246 MB
- SHA256:
- 8467c59c16ee9072a596ce2a1a84e835abdd163f11da48f4a0ee525942713a84
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.