Instructions to use MLbackup/Loras_2026_Backup with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MLbackup/Loras_2026_Backup 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/Loras_2026_Backup", 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
Download Samples/image (9).png from MLbackup/Loras_2026_Backup: direct link, hf CLI and curl.
- Browser
- Download file 3.7 MB
-
https://huggingface.co/MLbackup/Loras_2026_Backup/resolve/main/Samples/image%20(9).png
- Command line
-
hf download 'hf://MLbackup/Loras_2026_Backup/Samples/image (9).png'
-
curl -L -o 'image (9).png' 'https://huggingface.co/MLbackup/Loras_2026_Backup/resolve/main/Samples/image%20(9).png'
3.7 MB
.png)
- Xet hash:
- 2da436c081823e3b73690ce59e805322d989a0870c949c9738c5f90af9ee235f
- Size of remote file:
- 3.7 MB
- SHA256:
- d13d2a586d87ebb0750a5b5a9e33beddc7b0256768ac1b5fb5e2ded649a91d97
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