Supermaxman
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README.md
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@@ -42,21 +42,21 @@ Put in a detailed text prompt and generate Hubble Deep Space Images!
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> captures the moments after collapse, where the star has exploded and left an empty void in its
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> place, where a new black hole has emerged.
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![old.png](https://github.com/Supermaxman/
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> Hubble snaps images of the birthplace of stars within a cluster:
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> The dust and gas expand within the cluster due to the powerful influence of baby stars.
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> With these new images comes improved detail and a clearer view for astronomers to
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> study how early stars are born and change over time.
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![baby.png](https://github.com/Supermaxman/
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> Hubble image of galaxies colliding: The distorted spirals of two distant galaxies colliding are
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> captured here in a new image from the NASA/ESA Hubble Space Telescope. The typically symmetric
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> spirals common in spiral galaxies appear significantly warped, as the shape of both galaxies is torn
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> apart by their gravitational pulls.
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![collide.png](https://github.com/Supermaxman/
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## Model Details
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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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Also, be sure to check out the new and improved [Hubble Diffusion v2](https://huggingface.co/Supermaxman/hubble-diffusion-2)!
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image
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```
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![example.png](https://github.com/Supermaxman/
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## Model description
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- [Captioned Hubble Deep Space Scans dataset](https://huggingface.co/datasets/Supermaxman/esa-hubble)
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- [Model weights in Diffusers format](https://huggingface.co/Supermaxman/hubble-diffusion-1)
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- [Training code](https://github.com/Supermaxman/
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- [Hubble Diffusion v2](https://huggingface.co/Supermaxman/hubble-diffusion-2)
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Trained by [Maxwell Weinzierl](https://personal.utdallas.edu/~maxwell.weinzierl/) ([@Supermaxman1](https://twitter.com/Supermaxman1)).
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> captures the moments after collapse, where the star has exploded and left an empty void in its
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> place, where a new black hole has emerged.
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![old.png](https://github.com/Supermaxman/hubble-diffusion/blob/e76b22c805eea07e376f23ad12bb9ddecfd47cca/examples/hubble-diffusion-1/old.png?raw=true)
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> Hubble snaps images of the birthplace of stars within a cluster:
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> The dust and gas expand within the cluster due to the powerful influence of baby stars.
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> With these new images comes improved detail and a clearer view for astronomers to
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> study how early stars are born and change over time.
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![baby.png](https://github.com/Supermaxman/hubble-diffusion/blob/e76b22c805eea07e376f23ad12bb9ddecfd47cca/examples/hubble-diffusion-1/baby.png?raw=true)
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> Hubble image of galaxies colliding: The distorted spirals of two distant galaxies colliding are
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> captured here in a new image from the NASA/ESA Hubble Space Telescope. The typically symmetric
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> spirals common in spiral galaxies appear significantly warped, as the shape of both galaxies is torn
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> apart by their gravitational pulls.
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![collide.png](https://github.com/Supermaxman/hubble-diffusion/blob/e76b22c805eea07e376f23ad12bb9ddecfd47cca/examples/hubble-diffusion-1/collide.png?raw=true)
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## Model Details
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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), with initial weights from [CompVis/stable-diffusion-v1-4](https://huggingface.co/CompVis/stable-diffusion-v1-4). It was fine-tuned on [Supermaxman/esa-hubble](https://huggingface.co/datasets/Supermaxman/esa-hubble).
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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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```bibtex
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@misc{weinzierl2023sdhubble1,
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author = {Weinzierl, Maxwell A.},
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title = {Hubble Diffusion v1: Stable Diffusion v1.4 fine tuned on ESA Hubble Deep Space Images & Captions},
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year={2023},
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howpublished= {\url{https://huggingface.co/Supermaxman/hubble-diffusion-1}}
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}
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```
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Also, be sure to check out the new and improved [Hubble Diffusion v2](https://huggingface.co/Supermaxman/hubble-diffusion-2)!
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image
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```
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![example.png](https://github.com/Supermaxman/hubble-diffusion/blob/e76b22c805eea07e376f23ad12bb9ddecfd47cca/examples/hubble-diffusion-1/example.png?raw=true)
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## Model description
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- [Captioned Hubble Deep Space Scans dataset](https://huggingface.co/datasets/Supermaxman/esa-hubble)
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- [Model weights in Diffusers format](https://huggingface.co/Supermaxman/hubble-diffusion-1)
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- [Training code](https://github.com/Supermaxman/hubble-diffusion)
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- [Hubble Diffusion v2](https://huggingface.co/Supermaxman/hubble-diffusion-2)
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Trained by [Maxwell Weinzierl](https://personal.utdallas.edu/~maxwell.weinzierl/) ([@Supermaxman1](https://twitter.com/Supermaxman1)).
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