Instructions to use Muapi/vvikaelff with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/vvikaelff with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/vvikaelff") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download preview.jpg from Muapi/vvikaelff: direct link, hf CLI and curl.
- Browser
- Download file 186 kB
-
https://huggingface.co/Muapi/vvikaelff/resolve/main/preview.jpg
- Command line
-
hf download hf://Muapi/vvikaelff/preview.jpg
-
curl -L -o preview.jpg https://huggingface.co/Muapi/vvikaelff/resolve/main/preview.jpg
186 kB

- Xet hash:
- 5fcb4c69b29ed242528205891a444236189523e836abba0eb4d21aba0eaf98c6
- Size of remote file:
- 186 kB
- SHA256:
- f9304552116e6a4c6e685e1947e7567254ae7d143c9ec235e5becf290cf2d133
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.