Instructions to use suryatmodulus/MOSS-Image-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use suryatmodulus/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("suryatmodulus/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
Download assets/showcase/layout-bboxes.webp from suryatmodulus/MOSS-Image-Base: direct link, hf CLI and curl.
- Browser
- Download file 851 kB
-
https://huggingface.co/suryatmodulus/MOSS-Image-Base/resolve/main/assets/showcase/layout-bboxes.webp
- Command line
-
hf download hf://suryatmodulus/MOSS-Image-Base/assets/showcase/layout-bboxes.webp
-
curl -L -o layout-bboxes.webp https://huggingface.co/suryatmodulus/MOSS-Image-Base/resolve/main/assets/showcase/layout-bboxes.webp
851 kB

- Xet hash:
- 5fa254b3d8c6f21fa9d349f252976dba743e6db3c624f6dd96e0e4009c49dabf
- Size of remote file:
- 851 kB
- SHA256:
- 0cd091fbd9145b9dc640e1d70dc10e6776b661bb1f443bdefadc9a24f78214d1
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