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README.md
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license:
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---
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<img src="pixcell_256_cell_controlnet_banner.png" alt="pixcell_256_cell_controlnet_banner" width="500"/>
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uncond = pipeline.get_unconditional_embedding(uni_emb.shape[0])
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# Generate new samples using the given mask
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samples = pipeline(uni_embeds=uni_emb, controlnet_input=mask, negative_uni_embeds=uncond, guidance_scale=2.5, num_images_per_prompt=1).images
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```
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license: cc-by-nc-nd-4.0
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<img src="pixcell_256_cell_controlnet_banner.png" alt="pixcell_256_cell_controlnet_banner" width="500"/>
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uncond = pipeline.get_unconditional_embedding(uni_emb.shape[0])
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# Generate new samples using the given mask
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samples = pipeline(uni_embeds=uni_emb, controlnet_input=mask, negative_uni_embeds=uncond, guidance_scale=2.5, num_images_per_prompt=1).images
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```
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### License & Usage
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**License**: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
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**Notice**: This model is a derivative work conditioned on embeddings from the [[UNI-2h]](https://huggingface.co/MahmoodLab/UNI2-h) foundation model. As such, it is subject to the original terms of the UNI2 license.
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- Academic & Research Use Only: You may use these weights for non-commercial research purposes.
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- No Commercial Use: You may not use this model for any commercial purpose, including product development or commercial services.
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