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README.md
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---
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license: openrail++
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---
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---
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license: openrail++
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language:
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- en
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tags:
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- stable-diffusion
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- stable-diffusion-diffusers
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- text-to-image
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widget:
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- text: "Hubble snaps images of the birthplace of stars within a cluster: The dust and gas expand within the cluster due to the powerful influence of baby stars. With these new images comes improved detail and a clearer view for astronomers to study how early stars are born and change over time."
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example_title: Baby Stars
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- text: "Hubble captures the death of a star: Old stars, nearing the end of their life, collapse under the weight of their own gravity and the outer layers explode as a 'supernova'. In this image Hubble captures the moments after collapse, where the star has exploded and left an empty void in its place, where a new black hole has emerged."
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example_title: Old Stars
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- text: "Hubble image of galaxies colliding: The distorted spirals of two distant galaxies colliding are captured here in a new image from the NASA/ESA Hubble Space Telescope. The typically symmetric spirals common in spiral galaxies appear significantly warped, as the shape of both galaxies is torn apart by their gravitational pulls."
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example_title: Galaxies Collide
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- text: "Pink-tinted plumes in the Large Magellanic Cloud: The aggressively pink plumes seen in this image are extremely uncommon, with purple-tinted currents and nebulous strands reaching out into the surrounding space."
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example_title: Pink Plumes
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- text: "The stellar plasma of Wolf 359: The red dwarf star Wolf 359 from the constellation Leo is captured in extreme detail in a new image from the NASA/ESA Hubble Space Telescope. Wolf 359, classified as a M6 red dwarf, has certain peculiar qualities indicated by an unusual ejection of plasma. The Hubble telescope was able to capture one such event"
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example_title: Wolf 359
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thumbnail: ""
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inference: true
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datasets:
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- Supermaxman/esa-hubble
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---
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# Hubble Diffusion v2: Stable Diffusion v2.1 fine tuned on ESA Hubble Deep Space Images & Captions
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Put in a detailed text prompt and generate high-quality Hubble Deep Space Images! Now with Stable Diffusion 2.1!
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> Hubble captures the death of a star: Old stars, nearing the end of their life, collapse under the
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> weight of their own gravity and the outer layers explode as a 'supernova'. In this image Hubble
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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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> Pink-tinted plumes in the Large Magellanic Cloud:
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> The aggressively pink plumes seen in this image are extremely uncommon,
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> with purple-tinted currents and nebulous strands reaching out into the surrounding space.
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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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+

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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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> The stellar plasma of Wolf 359: The red dwarf star Wolf 359 from the constellation Leo is captured in extreme detail in a new image from the NASA/ESA Hubble Space Telescope.
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> Wolf 359, classified as a M6 red dwarf, has certain peculiar qualities indicated by an unusual ejection of plasma. The Hubble telescope was able to capture one such event
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## Model Details
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- **Developed by:** Maxwell Weinzierl
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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:** [CreativeML Open RAIL++-M License](https://huggingface.co/stabilityai/stable-diffusion-2/blob/main/LICENSE-MODEL)
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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 ([OpenCLIP-ViT/H](https://github.com/mlfoundations/open_clip)).
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- **Resources for more information:** [GitHub Repository](https://github.com/Stability-AI/).
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- **Cite as:**
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@misc{weinzierl2023sdhubble2,
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author = {Weinzierl, Maxwell A.},
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title = {Hubble Diffusion v2: Stable Diffusion v2.1 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-2}}
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}
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Also, be sure to check out the prior version [Hubble Diffusion v1](https://huggingface.co/Supermaxman/hubble-diffusion-1)!
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## Examples
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We recommend using [🤗's Diffusers library](https://github.com/huggingface/diffusers) to run Hubble Diffusion.
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### Usage
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```bash
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pip install transformers diffusers accelerate
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```
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```python
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import torch
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from diffusers import StableDiffusionPipeline
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model_id = "Supermaxman/hubble-diffusion-2"
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pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
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pipe = pipe.to("cuda")
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# saves significant GPU memory for small inference cost
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pipe.enable_attention_slicing()
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prompt = "Hubble snaps images of the birthplace of stars within a cluster: The dust and gas expand within the cluster due to the powerful influence of baby stars. With these new images comes improved detail and a clearer view for astronomers to study how early stars are born and change over time."
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image = pipe(prompt).images[0]
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image
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```
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## Model description
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Trained on [ESA Hubble Deep Space Images & Captions](https://huggingface.co/datasets/Supermaxman/esa-hubble) using [Google Colab Pro](https://colab.research.google.com/signup) with a single A100 GPU for around 33,000 steps (about 12 hours, at a cost of about $20).
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## Links
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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-2)
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- [Training code](https://github.com/Supermaxman/HubbleDiffuser)
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- [Hubble Diffusion v1](https://huggingface.co/Supermaxman/hubble-diffusion-1)
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Trained by [Maxwell Weinzierl](https://personal.utdallas.edu/~maxwell.weinzierl/) ([@Supermaxman1](https://twitter.com/Supermaxman1)).
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## Citation
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```bibtex
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@misc{weinzierl2023sdhubble2,
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author = {Weinzierl, Maxwell A.},
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title = {Hubble Diffusion v2: Stable Diffusion v2.1 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-2}}
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}
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```
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