Instructions to use darask0/MOSS-Image_4-step_adapter_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use darask0/MOSS-Image_4-step_adapter_lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("OpenMOSS-Team/MOSS-Image-SFT", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("darask0/MOSS-Image_4-step_adapter_lora") 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 images/training/000500.jpg from darask0/MOSS-Image_4-step_adapter_lora: direct link, hf CLI and curl.
- Browser
- Download file 442 kB
-
https://huggingface.co/darask0/MOSS-Image_4-step_adapter_lora/resolve/main/images/training/000500.jpg
- Command line
-
hf download hf://darask0/MOSS-Image_4-step_adapter_lora/images/training/000500.jpg
-
curl -L -o 000500.jpg https://huggingface.co/darask0/MOSS-Image_4-step_adapter_lora/resolve/main/images/training/000500.jpg
442 kB

- Xet hash:
- fde20174ade496773fee16446afd83e0e98a144b7b51280864005ecb326f0f8a
- Size of remote file:
- 442 kB
- SHA256:
- d1bcacee6ee9a4f7820ca17eb638463d3bce61b25523e1c17782c12f8d7a1a34
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