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README.md
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@@ -47,7 +47,7 @@ Source code is available at https://github.com/NVlabs/Sana.
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- **Model type:** Linear-Diffusion-Transformer-based text-to-image generative model
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- **Model size:** 1648M parameters
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- **Model resolution:** This model is developed to generate 1024px based images with multi-scale heigh and width.
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- **License:** [
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- **Model Description:** This is a model that can be used to generate and modify images based on text prompts.
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It is a Linear Diffusion Transformer that uses one fixed, pretrained text encoders ([Gemma2-2B-IT](https://huggingface.co/google/gemma-2-2b-it))
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and one 32x spatial-compressed latent feature encoder ([DC-AE](https://hanlab.mit.edu/projects/dc-ae)).
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- **Model type:** Linear-Diffusion-Transformer-based text-to-image generative model
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- **Model size:** 1648M parameters
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- **Model resolution:** This model is developed to generate 1024px based images with multi-scale heigh and width.
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- **License:** [NSCL v2-custom](./LICENSE.txt). Governing Terms: NVIDIA License. Additional Information: [Gemma Terms of Use | Google AI for Developers](https://ai.google.dev/gemma/terms) for Gemma-2-2B-IT, [Gemma Prohibited Use Policy | Google AI for Developers](https://ai.google.dev/gemma/prohibited_use_policy).
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- **Model Description:** This is a model that can be used to generate and modify images based on text prompts.
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It is a Linear Diffusion Transformer that uses one fixed, pretrained text encoders ([Gemma2-2B-IT](https://huggingface.co/google/gemma-2-2b-it))
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and one 32x spatial-compressed latent feature encoder ([DC-AE](https://hanlab.mit.edu/projects/dc-ae)).
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