Instructions to use SD-Next/MOSS-Image-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SD-Next/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("SD-Next/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
Upload README.md with huggingface_hub
Browse files
README.md
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- diffusers
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- text-to-image
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# MOSS-Image-Base
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<div align="center">
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- diffusers
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# MOSS-Image-Base (SD.Next Mirror)
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Mirror of **[OpenMOSS-Team/MOSS-Image-Base](https://huggingface.co/OpenMOSS-Team/MOSS-Image-Base)** at revision `5f40f07a`, kept for use with [SD.Next](https://github.com/vladmandic/sdnext).
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Please find the original repository [here](https://huggingface.co/OpenMOSS-Team/MOSS-Image-Base).
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- Transformer, VAE, text encoder, tokenizer, scheduler and the bundled `pipeline_moss_image.py` are unchanged from the original repository.
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- License: Apache License 2.0 (see LICENSE).
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Loads in [SD.Next](https://github.com/vladmandic/sdnext) from the Models reference list, or in diffusers with the bundled `pipeline_moss_image` custom pipeline.
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# MOSS-Image-Base
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<div align="center">
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