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 (69).png from MLbackup/Loras_2026_Backup: direct link, hf CLI and curl.
- Browser
- Download file 4.08 MB
-
https://huggingface.co/MLbackup/Loras_2026_Backup/resolve/main/Samples/image%20(69).png
- Command line
-
hf download 'hf://MLbackup/Loras_2026_Backup/Samples/image (69).png'
-
curl -L -o 'image (69).png' 'https://huggingface.co/MLbackup/Loras_2026_Backup/resolve/main/Samples/image%20(69).png'
4.08 MB
.png)
- Xet hash:
- 448537dedc5ac969a53c4b9d0ef75849134d101c7cd7e88da572d3d9483b37fe
- Size of remote file:
- 4.08 MB
- SHA256:
- 8bfb53b5bc6b07f6b2603a07452f938f5042403957f2332d154b6b408192adf4
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