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README.md CHANGED
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- license: apache-2.0
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  # Uses
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  ## Direct Use
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  ### Intel’s Human Rights Disclaimer:
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- Intel is committed to respecting human rights and avoiding complicity in human rights abuses. See Intel's Global Human Rights Principles. Intel's products and software are intended only to be used in applications that do not cause or contribute to a violation of an internationally recognized human right.
 
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+ license: creativeml-openrail-m
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+ extra_gated_prompt: |-
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+ This model is open access and available to all, with a CreativeML OpenRAIL-M license further specifying rights and usage.
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+ The CreativeML OpenRAIL License specifies:
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+ 1. You can't use the model to deliberately produce nor share illegal or harmful outputs or content
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+ 2. Intel claims no rights on the outputs you generate, you are free to use them and are accountable for their use which must not go against the provisions set in the license
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+ 3. You may re-distribute the weights and use the model commercially and/or as a service. If you do, please be aware you have to include the same use restrictions as the ones in the license and share a copy of the CreativeML OpenRAIL-M to all your users (please read the license entirely and carefully)
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+ Please read the full license carefully here: https://huggingface.co/spaces/CompVis/stable-diffusion-license
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+
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+ extra_gated_heading: Please read the LICENSE to access this model
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  ---
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+ # SD v1-5 square Model Card
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+ The original source of this model is : [runwayml/stable-diffusion-v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5).
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+ This model is just optimized and converted to Intermediate Representation (IR) using OpenVino's Model Optimizer and POT tool to run on Intel's Hardware - CPU, GPU, NPU.
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+
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+ We have FP16 and INT8 versions of the model. Please note currently only unet model is quantized to int8.
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+
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+ Intended to be used with:
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+ - GIMP plugin [openvino-ai-plugins-gimp](https://github.com/intel/openvino-ai-plugins-gimp.git)
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+ - Blender Addon [dream-textures-openvino](https://github.com/intel/dream-textures-openvino)
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+
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+ ## Original Model Details
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+ - **Original Developed by:** Robin Rombach, Patrick Esser
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+ - **Model type:** Diffusion-based text-to-image generation model
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+ - **Language(s):** English
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+ - **License:** [The CreativeML OpenRAIL M license](https://huggingface.co/spaces/CompVis/stable-diffusion-license) is an [Open RAIL M license](https://www.licenses.ai/blog/2022/8/18/naming-convention-of-responsible-ai-licenses), adapted from the work that [BigScience](https://bigscience.huggingface.co/) and [the RAIL Initiative](https://www.licenses.ai/) are jointly carrying in the area of responsible AI licensing. See also [the article about the BLOOM Open RAIL license](https://bigscience.huggingface.co/blog/the-bigscience-rail-license) on which our license is based.
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+ - **Model Description:** This is a model that can be used to generate and modify images based on text prompts. It is a [Latent Diffusion Model](https://arxiv.org/abs/2112.10752) that uses a fixed, pretrained text encoder ([CLIP ViT-L/14](https://arxiv.org/abs/2103.00020)) as suggested in the [Imagen paper](https://arxiv.org/abs/2205.11487).
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+ - **Resources for more information:** [GitHub Repository](https://github.com/CompVis/stable-diffusion), [Paper](https://arxiv.org/abs/2112.10752).
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+ - **Cite as:**
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+
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+ @InProceedings{Rombach_2022_CVPR,
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+ author = {Rombach, Robin and Blattmann, Andreas and Lorenz, Dominik and Esser, Patrick and Ommer, Bj\"orn},
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+ title = {High-Resolution Image Synthesis With Latent Diffusion Models},
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+ booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
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+ month = {June},
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+ year = {2022},
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+ pages = {10684-10695}
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+ }
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+
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+
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  # Uses
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  ## Direct Use
 
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  ### Intel’s Human Rights Disclaimer:
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+ Intel is committed to respecting human rights and avoiding complicity in human rights abuses. See Intel's Global Human Rights Principles. Intel's products and software are intended only to be used in applications that do not cause or contribute to a violation of an internationally recognized human right.
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