Instructions to use yeq6x/Image2PositionMap_v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use yeq6x/Image2PositionMap_v3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("yeq6x/Image2PositionMap_v3", 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
- Xet hash:
- 4843f3f22f5b778b90313355c9632ec416acc9d423d820113b87168d529165c9
- Size of remote file:
- 10 GB
- SHA256:
- 8f90b64af72d4dd31dc8474902ff34ce2d23706bc4ee731da0f0bbb2cbfa45ff
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