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:
- f07ec59bbc2404b7644e273a7c38f2b3020bd1f1b88883ae7f1b1c39496c280f
- Size of remote file:
- 455 MB
- SHA256:
- bff8bf01bbf7ca6ed87565c2e0beecd8a71097ecf324f9197bf75151e9ba97a8
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