Instructions to use KevinMoby/TrainK1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use KevinMoby/TrainK1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("KevinMoby/TrainK1", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 149a2f25cfbaa94374fde60fdcdbe83cc6f25548db86c36b2c58731f59ba8777
- Size of remote file:
- 3.29 MB
- SHA256:
- dbd813a3137a4c693576ebfbecb468b6ae3299ca13affa3d1a31dcac35e402ca
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