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", torch_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:
- fca3ea8aad9acf6a2d3a15dabde6f8b51d345693336cc48283c71cdce60a579f
- Size of remote file:
- 19.3 MB
- SHA256:
- 5ea80d381b8cd3af6010a3023720d705df3ff5492e5265f2f0e90339e860759e
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