Instructions to use MLbackup/9_2025 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MLbackup/9_2025 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MLbackup/9_2025", 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:
- f28ba2445516623f9053723a7a83b7544236018db8b63d19ea4988bd8b2d0937
- Size of remote file:
- 6.94 GB
- SHA256:
- 556e72078fca99555ba72f3116301f17089de7b65a22613cc2225581355bf56a
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