Instructions to use Muapi/cardboard with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/cardboard 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/cardboard") 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/cardboard: direct link, hf CLI and curl.
- Browser
- Download file 285 kB
-
https://huggingface.co/Muapi/cardboard/resolve/main/preview.jpg
- Command line
-
hf download hf://Muapi/cardboard/preview.jpg
-
curl -L -o preview.jpg https://huggingface.co/Muapi/cardboard/resolve/main/preview.jpg
285 kB

- Xet hash:
- 15f82c6a05f3b82434979e0263f8a9dcd828d60095cc84e55480184364044f1f
- Size of remote file:
- 285 kB
- SHA256:
- 40ce5386954d56ec46510b6e0dc2627f12f919819e0e7f110d8e83af6fa236c3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.