Instructions to use maxpmx/pathmnist_train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use maxpmx/pathmnist_train 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_train", 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:
- 89478c4eef150053d92a18ac1358d79bb302e78bd10a580b44cf210368be606a
- Size of remote file:
- 910 MB
- SHA256:
- 8b97a7934d7b019308e08def4f772244df306362f356a8f49201f2900b730bb9
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