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---
license: creativeml-openrail-m
tags:
- pytorch
- diffusers
- stable-diffusion
- text-to-image
- diffusion-models-class
- dreambooth-hackathon
- science
widget:
- text: Photorealistic trex dinosaur, (Jurassic Park) lush greenery, towering prehistoric
ferns, dramatic lighting casting shadows, (intense expression), rugged texture
of scales, ferocious stance, misty atmosphere, high-quality detail, 4K, (cinematic
depth), vibrant colors of nature, embedding a sense of ancient history, (dynamic
environment) teeming with life and excitement.
---
# A DreamBooth model capable of spectacular/cinematic visuals of Tyrannosaurus rex (the most famous and feared of all prehistoric predators) dinosaur image generator.
Trained by HugeFighter on the HugeFighter/dinosaurs dataset, This is a Stable Diffusion model fine-tuned on the dinosaur concept with DreamBooth.
It can be used by modifying the `instance_prompt`: **a photo of a trex dinosaur**
This model was created as part of the DreamBooth Hackathon 🔥. Visit the [organisation page](https://huggingface.co/dreambooth-hackathon) for instructions on how to take part!
## Description
This is a Stable Diffusion model fine-tuned on `dinosaur` images for the science theme.
## Usage
```python
from diffusers import StableDiffusionPipeline
pipeline = StableDiffusionPipeline.from_pretrained('HugeFighter/trex-dinosaur')
image = pipeline().images[0]
image
```
### Dataset Summary: T.Rex generator
This dataset includes 12 images of trex collected randomly from web.
The dataset contains unique photographs of trex with different backgrounds.
I won't recommend this using these images as your training data (small dataset), but you can still use it for sampling purpose.
The dataset is intended to be used in the context of the Hugging Face Dream Booth hackathon, a competition that challenges participants to build innovative applications using the Hugging Face transformers library. The submission is for the category of animal.
## Dataset Structure
The complete dataset consists of 12 objects, representing 0.01GB of stored data across 12 rows in parquet format.
# Examples of output images generated by pipeline
prompt = "A photo of a trex dinosaur, wandering over Jurassic park with a big roar"
prompt = "Photorealistic trex dinosaur, (Jurassic Park) lush greenery, towering prehistoric ferns, dramatic lighting casting shadows, (intense expression), rugged texture of scales, ferocious stance, misty atmosphere, high-quality detail, 4K, (cinematic depth), vibrant colors of nature, embedding a sense of ancient history, (dynamic environment) teeming with life and excitement."
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