# min(DALL·E)

[![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)

This is a minimal implementation of Boris Dayma's [DALL·E Mini](https://github.com/borisdayma/dalle-mini).  It has been stripped to the bare essentials necessary for doing inference, and converted to PyTorch.  To run the torch model, the only third party dependencies are numpy and torch.

It currently takes **7.4 seconds** to generate an image with DALL·E Mega with PyTorch on a standard GPU runtime in Colab

### Setup

Run either `sh setup_torch.sh` or `sh setup_flax.sh` to install dependencies and download pretrained models.  The torch models can be manually downloaded [here](https://huggingface.co/kuprel/min-dalle).
The flax models can be manually downloaded here: 
[VQGan](https://huggingface.co/dalle-mini/vqgan_imagenet_f16_16384), 
[DALL·E Mini](https://wandb.ai/dalle-mini/dalle-mini/artifacts/DalleBart_model/mini-1/v0/files), 
[DALL·E Mega](https://wandb.ai/dalle-mini/dalle-mini/artifacts/DalleBart_model/mega-1-fp16/v14/files)

### 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 either `MinDalleTorch` or `MinDalleFlax`, then call `generate_image` with some text and a seed.  See the colab for an example.

### Examples

```
python image_from_text.py --text='artificial intelligence' --torch
```
![Alien](examples/artificial_intelligence.png)


```
python image_from_text.py --text='a comfy chair that looks like an avocado' --torch --mega --seed=10
```
![Avocado Armchair](examples/avocado_armchair.png)


```
python image_from_text.py --text='court sketch of godzilla on trial' --torch --mega --seed=40
```

![Godzilla Trial](examples/godzilla_trial.png)