Instructions to use OpenMOSS-Team/MOSS-Image-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use OpenMOSS-Team/MOSS-Image-Base 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-Base", 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
I've trained primitive i2i lora in an hour but already works nice
#6
by sorryhyun - opened
Hi, it feels a bit promoting by myself, but I wanted to share about this. I realized that qwen3.5 shows nice vision capability and there's reference dimension in moss model, I tried training a simple i2i task, colorizing manga image.
The approach was quite simple. I fed qwen(image, caption), vae(downscale(image, 2)) as source and image as target, and trained about an hour with local 5070ti, and the result is as below:
I uploaded lora weight and workflow in here and comfyui repo in here and training code is in here Anyway thanks for this excellent model.
