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# min(DALL·E)
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[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/kuprel/min-dalle/blob/main/min_dalle.ipynb)  
[![Replicate](https://replicate.com/kuprel/min-dalle/badge)](https://replicate.com/kuprel/min-dalle)
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This is a minimal implementation of Boris Dayma's [DALL·E Mini](https://github.com/borisdayma/dalle-mini) in PyTorch. It has been stripped to the bare essentials necessary for doing inference. The only third party dependencies are numpy and torch.
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It currently takes **7.4 seconds** to generate an image with DALL·E Mega with PyTorch on a standard GPU runtime in Colab
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The flax model, and the code for coverting it to torch, have been moved [here](https://github.com/kuprel/min-dalle-flax).
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### Install
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```$ pip install min-dalle```
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### Usage
Use the python script `image_from_text.py` to generate images from the command line. Note: the command line script loads the models and parameters each time. To load a model once and generate multiple times, initialize `MinDalleTorch`, then call `generate_image` with some text and a seed. See the colab for an example.
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Model parameters will be downloaded as needed to the directory specified. The models can also be manually downloaded [here](https://huggingface.co/kuprel/min-dalle/tree/main).
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### Examples
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```
python image_from_text.py --text='artificial intelligence' --seed=7
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```
![Alien](examples/artificial_intelligence.png)
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```
python image_from_text.py --text='a comfy chair that looks like an avocado' --mega --seed=10
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```
![Avocado Armchair](examples/avocado_armchair.png)
```
python image_from_text.py --text='court sketch of godzilla on trial' --mega --seed=40
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```
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![Godzilla Trial](examples/godzilla_on_trial.png)
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```
python image_from_text.py --text='trail cam footage of gollum eating watermelon' --mega --seed=1
```
![Gollum Trailcam](examples/gollum_trailcam.png)