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:
- 4e44da17fe49d0a82cb51ddb01ac317002ffb4e086a1bd56e5ad5f088f1c2543
- Size of remote file:
- 6.94 GB
- SHA256:
- dba7a6b66cfe6bf4100bdc0900c66a73620a1542ae93e750472167e5289cf9f1
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