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:
- 06c43698233820597cba1bc82608c869180e7fbdf973418b1d3c00ae7933e395
- Size of remote file:
- 910 MB
- SHA256:
- e599c554453c0cc26b6a9ee5f71a53006a0f7f8519f0df4c5d65077813d5f914
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