Instructions to use duja1/mjjjj with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use duja1/mjjjj with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("duja1/mjjjj", 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 text_encoder/pytorch_model.bin from duja1/mjjjj: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/duja1/mjjjj/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://duja1/mjjjj/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/duja1/mjjjj/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- f6c99424ecbf3dae84ea8a02e5efe304801b1b1b1a02138ea8613f0d65993d3b
- Size of remote file:
- 492 MB
- SHA256:
- 0f5bbc5f473c789f3274509512f8e1fa932b9006e01fcdf017cc8723c7d17fa8
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