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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- ffc64be0e004b62154c2ef0181c4b4ac28fc87f88cc5ef9bdd4bc5b65a4faadf
- Size of remote file:
- 6.94 GB
- SHA256:
- bdd5ee277ace04c785c7895c224e2c04b29bda55ccfee246739a189041c979e7
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