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
Upload via HuggingFaceUploader Widget 🤗 (file 4/5: VdiffRemixsept2025.fp16.safetensors)
c3edc48 verified - Xet hash:
- dfc2d48c6328c72d729a496c1c55301220331e9ebc8aea0a91973af62f6a6b54
- Size of remote file:
- 6.94 GB
- SHA256:
- 6d06d6d6f090f12f39e02b1143b754e12682b9a984b5362478a8dea5d9a217b5
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