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---
license: openrail++
language:
- en
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
widget:
- 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."
example_title: Baby Stars
- 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."
example_title: Old Stars
- 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."
example_title: Galaxies Collide
- 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."
example_title: Pink Plumes
- 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"
example_title: Wolf 359
thumbnail: ""
inference: true
datasets:
- Supermaxman/esa-hubble
---
# Hubble Diffusion v2: Stable Diffusion v2.1 fine tuned on ESA Hubble Deep Space Images & Captions
Put in a detailed text prompt and generate high-quality Hubble Deep Space Images! Now with Stable Diffusion 2.1!
> 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.
> 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.
> 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.
> 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.
> 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
## Model Details
- **Developed by:** Maxwell Weinzierl
- **Model type:** Diffusion-based text-to-image generation model
- **Language(s):** English
- **License:** [CreativeML Open RAIL++-M License](https://huggingface.co/stabilityai/stable-diffusion-2/blob/main/LICENSE-MODEL)
- **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)).
- **Resources for more information:** [GitHub Repository](https://github.com/Stability-AI/).
- **Cite as:**
@misc{weinzierl2023sdhubble2,
author = {Weinzierl, Maxwell A.},
title = {Hubble Diffusion v2: Stable Diffusion v2.1 fine tuned on ESA Hubble Deep Space Images & Captions},
year={2023},
howpublished= {\url{https://huggingface.co/Supermaxman/hubble-diffusion-2}}
}
Also, be sure to check out the prior version [Hubble Diffusion v1](https://huggingface.co/Supermaxman/hubble-diffusion-1)!
## Examples
We recommend using [🤗's Diffusers library](https://github.com/huggingface/diffusers) to run Hubble Diffusion.
### Usage
```bash
pip install transformers diffusers accelerate
```
```python
import torch
from diffusers import StableDiffusionPipeline
model_id = "Supermaxman/hubble-diffusion-2"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to("cuda")
# saves significant GPU memory for small inference cost
pipe.enable_attention_slicing()
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."
image = pipe(prompt).images[0]
image
```
## Model description
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).
## Links
- [Captioned Hubble Deep Space Scans dataset](https://huggingface.co/datasets/Supermaxman/esa-hubble)
- [Model weights in Diffusers format](https://huggingface.co/Supermaxman/hubble-diffusion-2)
- [Training code](https://github.com/Supermaxman/HubbleDiffuser)
- [Hubble Diffusion v1](https://huggingface.co/Supermaxman/hubble-diffusion-1)
Trained by [Maxwell Weinzierl](https://personal.utdallas.edu/~maxwell.weinzierl/) ([@Supermaxman1](https://twitter.com/Supermaxman1)).
## Citation
```bibtex
@misc{weinzierl2023sdhubble2,
author = {Weinzierl, Maxwell A.},
title = {Hubble Diffusion v2: Stable Diffusion v2.1 fine tuned on ESA Hubble Deep Space Images & Captions},
year={2023},
howpublished= {\url{https://huggingface.co/Supermaxman/hubble-diffusion-2}}
}
```
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