Instructions to use edgetensor/max-schnell with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use edgetensor/max-schnell with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("edgetensor/max-schnell", 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
- Draw Things
- DiffusionBee
- Xet hash:
- e79c53e75277e9b59f9c24f9b9631c157ab8f93a66ac59809353e573390683c7
- Size of remote file:
- 9.52 GB
- SHA256:
- 565cb2487351282e8e4dbeb88e63f4ad28217ce0439f5a8e6525a924807d2d9b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.