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/000300.jpg from darask0/MOSS-Image_4-step_adapter_lora: direct link, hf CLI and curl.
- Browser
- Download file 430 kB
-
https://huggingface.co/darask0/MOSS-Image_4-step_adapter_lora/resolve/main/images/training/000300.jpg
- Command line
-
hf download hf://darask0/MOSS-Image_4-step_adapter_lora/images/training/000300.jpg
-
curl -L -o 000300.jpg https://huggingface.co/darask0/MOSS-Image_4-step_adapter_lora/resolve/main/images/training/000300.jpg
430 kB

- Xet hash:
- 96807d3a8971729416724faa769a4fa0ec87a88d709b71b93385e2498cb916d8
- Size of remote file:
- 430 kB
- SHA256:
- 7741b1a0d41ec3b8e0e6bc5d46553cca9972d433ac319617b6d0205c869db969
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