Instructions to use bunnycore/MOSSArt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bunnycore/MOSSArt 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("bunnycore/MOSSArt") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from bunnycore/MOSSArt: direct link, hf CLI and curl.
- Browser
- Download file 578 Bytes
-
https://huggingface.co/bunnycore/MOSSArt/resolve/main/README.md
- Command line
-
hf download hf://bunnycore/MOSSArt/README.md
-
curl -L -o README.md https://huggingface.co/bunnycore/MOSSArt/resolve/main/README.md
578 Bytes
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/moss-image_00072_.png
text: '-'
- output:
url: images/moss-image_00053_.png
text: '-'
base_model: OpenMOSS-Team/MOSS-Image-SFT
instance_prompt: null
license: apache-2.0
MossArt

- Prompt
- -

- Prompt
- -
Model description
Trained on hundreds of diverse styles of images, like art, anime, webtoon, and other styles.
This lora is agressive, so set strength to 0.2 to 0.4
Download model
Download them in the Files & versions tab.