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title: README |
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emoji: 🏃 |
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--- |
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<img src="https://github.com/dome272/Wuerstchen/assets/61938694/0617c863-165a-43ee-9303-2a17299a0cf9"> |
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Welcome to <b>WARP</b>. This is our little organization for multimodal generative models focussing on the visual domain. We have been working with generative image models a lot and |
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will soon work on video models as well. Our main team consists of: |
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- [Pablo Pernias](https://github.com/pabloppp/) |
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- [Dominic Rampas](https://github.com/dome272) |
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Feel free to join our [Discord](https://discord.gg/BTUAzb8vFY) channel! |
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Models: |
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<details> |
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<summary> |
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Paella |
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</summary> |
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<img src="https://user-images.githubusercontent.com/61938694/231021615-38df0a0a-d97e-4f7a-99d9-99952357b4b1.png" width=1200> |
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<ul> |
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<li>A simple & straightforward text-conditional image generation model that works on quantized latents.</li> |
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<li>More details can be found in the <a href="https://arxiv.org/abs/2211.07292v2">paper</a>, the <a href="https://laion.ai/blog/paella/">blog post</a> and the <a href="https://www.youtube.com/watch?v=zdE1I6kYKYc">YouTube video</a>.</li> |
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<li>Only accessible through <a href="https://github.com/dome272/Paella">GitHub</a>.</li> |
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</ul> |
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</details> |
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<details> |
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<summary> |
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Würstchen |
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</summary> |
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<ul> |
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<li>An efficient text-to-image model to train and use for inference. Achieves competetive performance to state-of-the-art methods, while needing only a fraction of the compute.</li> |
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<li>More details can be found in the <a href="https://arxiv.org/abs/2306.006372">paper</a>.</li> |
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<li>Versions:</li> |
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<ul> |
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<li>v1: Only accessible through <a href="https://github.com/dome272/Wuerstchen/">GitHub</a>.</li> |
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<li>v2: Accessible through <a href="https://github.com/dome272/Wuerstchen/">GitHub</a> and Diffusers</li> |
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</ul> |
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</ul> |
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</details> |
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