Instructions to use hvein/max_8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hvein/max_8 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hvein/max_8", 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:
- bc22043ff62b934fdc13abc0906b5f050fa2e79292bf7fead3fb9744b26ee5d5
- Size of remote file:
- 167 MB
- SHA256:
- 33c40ff3dc7adeb21dce76cd411d65828037efa0aa54432e3592418401cf8467
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