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:
- c2d3e3403e97afbc43424212ee13998e24bdf9f7f00d97936bce1dc78f9f55c3
- Size of remote file:
- 1.39 GB
- SHA256:
- 144edde441d0ad2e538f7c78884ab26647195e3b825fc7f1f242b58b8bfb57b5
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