Instructions to use Microguy1/MOSS-Image-Base-DUPLI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Microguy1/MOSS-Image-Base-DUPLI with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Microguy1/MOSS-Image-Base-DUPLI", 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 .gitattributes from Microguy1/MOSS-Image-Base-DUPLI: direct link, hf CLI and curl.
- Browser
- Download file 663 Bytes
-
https://huggingface.co/Microguy1/MOSS-Image-Base-DUPLI/resolve/main/.gitattributes
- Command line
-
hf download hf://Microguy1/MOSS-Image-Base-DUPLI/.gitattributes
-
curl -L -o .gitattributes https://huggingface.co/Microguy1/MOSS-Image-Base-DUPLI/resolve/main/.gitattributes
663 Bytes
| *.safetensors filter=lfs diff=lfs merge=lfs -text | |
| *.bin filter=lfs diff=lfs merge=lfs -text | |
| tokenizer/tokenizer.json filter=lfs diff=lfs merge=lfs -text | |
| assets/hero.png filter=lfs diff=lfs merge=lfs -text | |
| assets/showcase/layout-bboxes.webp filter=lfs diff=lfs merge=lfs -text | |
| assets/showcase/text-rendering.webp filter=lfs diff=lfs merge=lfs -text | |
| assets/teaser.webp filter=lfs diff=lfs merge=lfs -text | |
| assets/comparison/base.webp filter=lfs diff=lfs merge=lfs -text | |
| assets/comparison/sft.webp filter=lfs diff=lfs merge=lfs -text | |
| assets/showcase/overview.webp filter=lfs diff=lfs merge=lfs -text | |
| assets/showcase/overview2.webp filter=lfs diff=lfs merge=lfs -text | |