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:
- d9727612794d030263b2077a7d4a8290b787068cec65be61e9bc750481a000c0
- Size of remote file:
- 1 kB
- SHA256:
- 84a5850471d8279dd2cbf47393689548e6c452167f7bb2b167c27b57055c0463
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