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:
- 0a79f3540a466ee160ae68f1791196e294f455de611e9f2c6e4bcb7f104a7d69
- Size of remote file:
- 246 MB
- SHA256:
- 192a06f4ef7ece4acb33fc3c717790ee37b1f5d85e48e0dcac54dfea93e584a2
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