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:
- 009ac9c2c7ae15c1d2a89c8cf91e8f2482443fdb197dea28590e1c9f67c6ae06
- Size of remote file:
- 1.39 GB
- SHA256:
- 8841d5e4c05ce74941eb536ec3835f600cc82d36763fc5f30c69d09a886158c9
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