Instructions to use kmpartner/bk-testop with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kmpartner/bk-testop with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kmpartner/bk-testop", 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:
- c89bb710f0b34d1d3d650cf33c196f4d1dd535945c41a44af2b032a3759edeed
- Size of remote file:
- 681 MB
- SHA256:
- 5ee67f13de719e6c72334b4a066852d43dde1b050b11b78983f12f5f8d5553d8
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