min-dalle-test/README.md

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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)
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This is a minimal implementation of [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. The only third party dependencies are `numpy` and `torch` for the torch model and `flax` for the flax model.
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### Setup
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Run `sh setup.sh` to install dependencies and download pretrained models. In the bash script, Git LFS is used to download the VQGan detokenizer from Hugging Face and the Weight & Biases python package is used to download the DALL·E Mini and DALL·E Mega transformer models. These models can also be downloaded manually:
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[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)
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### Usage
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Use the command line python script `image_from_text.py` to generate images. Here are some examples:
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```
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python image_from_text.py --text='alien life' --seed=7
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```
![Alien](examples/alien.png)
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```
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python image_from_text.py --text='a comfy chair that looks like an avocado' --mega --seed=4
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```
![Avocado Armchair](examples/avocado_armchair.png)
```
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python image_from_text.py --text='court sketch of godzilla on trial' --mega --seed=100
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```
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![Godzilla Trial](examples/godzilla_trial.png)