Efficient-Large-Model
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Sana_1600M_1024px_BF16

1024px_based_image_size

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Lawrence-cj commited on 17 days ago

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@@ -48,7 +48,7 @@ Source code is available at https://github.com/NVlabs/Sana.
 - **Model size:** 1648M parameters
 - **Model precision:** torch.bfloat16 (BF16)
 - **Model resolution:** This model is developed to generate 1024px based images with multi-scale heigh and width.
-- **License:** [CC BY-NC-SA 4.0 License](./LICENSE.txt)
 - **Model Description:** This is a model that can be used to generate and modify images based on text prompts.
 It is a Linear Diffusion Transformer that uses one fixed, pretrained text encoders ([Gemma2-2B-IT](https://huggingface.co/google/gemma-2-2b-it))
 and one 32x spatial-compressed latent feature encoder ([DC-AE](https://hanlab.mit.edu/projects/dc-ae)).

 - **Model size:** 1648M parameters
 - **Model precision:** torch.bfloat16 (BF16)
 - **Model resolution:** This model is developed to generate 1024px based images with multi-scale heigh and width.
+- **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).
 - **Model Description:** This is a model that can be used to generate and modify images based on text prompts.
 It is a Linear Diffusion Transformer that uses one fixed, pretrained text encoders ([Gemma2-2B-IT](https://huggingface.co/google/gemma-2-2b-it))
 and one 32x spatial-compressed latent feature encoder ([DC-AE](https://hanlab.mit.edu/projects/dc-ae)).