Instructions to use DynamicXLAB/PhotoPoster with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DynamicXLAB/PhotoPoster with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("DynamicXLAB/PhotoPoster", 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:
- ea9862185ad2bc1ff8fc1d1a84715c70320f564979f6c9bc3271bb6f21da3eaf
- Size of remote file:
- 1.46 GB
- SHA256:
- 70bfbf1caeb9359aa7346c2c2f1913bf291cb7e6fca1a8e61cfe9ee987a343a9
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