Instructions to use showlab/show-o with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use showlab/show-o with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("showlab/show-o", 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
Add link to paper, improve formatting
Browse filesThis PR adds a link to the paper and improves formatting.
README.md
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- pytorch_model_hub_mixin
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This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration
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This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration.
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* Library: <https://github.com/showlab/Show-o>
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* Paper: [Show-o2: Improved Native Unified Multimodal Models](https://huggingface.co/papers/2506.15564)
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* Arxiv: https://arxiv.org/abs/2408.12528v2
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* Docs: [More Information Needed]
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