Instructions to use MLbackup/Flux_Scrape_Loras with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MLbackup/Flux_Scrape_Loras 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/Flux_Scrape_Loras", 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
- Xet hash:
- 3bfffd7409d31e316383131fb6dfaff60f16f951750368b708d38df086902844
- Size of remote file:
- 17 MB
- SHA256:
- 0fe343141533600bc718cf02f4a59f8eaabad2b3f49b358fad3d1e519350d1ed
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