Instructions to use SimpleTuner/moss-image-base-domokun-1024 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SimpleTuner/moss-image-base-domokun-1024 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") pipe.load_lora_weights("SimpleTuner/moss-image-base-domokun-1024") 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
Publish MOSS-Image experiment recipes, adapter checkpoints, and validation previews
Browse files
README.md
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Part of the [MOSS-Image LoRA experiments](https://huggingface.co/SimpleTuner/moss-image-LoRA-experiments).
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Training status: **training**, 5,
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Captions: original filename captions. Each run starts fresh from its released checkpoint, without an assistant LoRA.
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Resolution is 1024px equivalent image area with aspect ratios preserved.
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Part of the [MOSS-Image LoRA experiments](https://huggingface.co/SimpleTuner/moss-image-LoRA-experiments).
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Training status: **training**, 5,480 / 10,000 observed updates.
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Captions: original filename captions. Each run starts fresh from its released checkpoint, without an assistant LoRA.
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Resolution is 1024px equivalent image area with aspect ratios preserved.
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