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:
- 0fc6ea51b09cda5e4b82a486d1dfc0fd03cd01cb2765b67ed3be05e09f449ce7
- Size of remote file:
- 455 MB
- SHA256:
- 924e2fdd8b1044b2d32e3d2ca8bd60ee3bab836336ec80cd79f6f71645c1b361
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