Instructions to use maxpmx/pathmnist_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use maxpmx/pathmnist_test with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("maxpmx/pathmnist_test", 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:
- cedab8e8fec6ea75f8c41185f343fe2b4992b30542c53a1d8b7bc837d9cb7056
- Size of remote file:
- 455 MB
- SHA256:
- 5bae65fe1cfb655ce5c396c94c9abdb612f51e50707b1ab6e754dbfe9c9ebc43
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.