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# min(DALL·E) # 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(DALL·E).ipynb) [![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)
This is a minimal implementation of [DALL·E Mini](https://github.com/borisdayma/dalle-mini) in both Flax and PyTorch This is a minimal implementation of [DALL·E Mini](https://github.com/borisdayma/dalle-mini) in both Flax and PyTorch
### Setup ### Setup
Run `sh setup.sh` to install dependencies and download pretrained models. The only required dependencies are `flax` and `torch`. In the bash script, GitHub LFS is used to download the VQGan detokenizer 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: Run `sh setup.sh` to install dependencies and download pretrained models. The only required dependencies are `flax` and `torch`. In the bash script, GitHub LFS is used to download the VQGan detokenizer 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:
[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)
VQGan: https://huggingface.co/dalle-mini/vqgan_imagenet_f16_16384 ### Usage
DALL·E Mini: https://wandb.ai/dalle-mini/dalle-mini/artifacts/DalleBart_model/mini-1/v0/files Use the command line python script `image_from_text.py` to generate images. Here are some examples:
DALL·E Mega: https://wandb.ai/dalle-mini/dalle-mini/artifacts/DalleBart_model/mega-1-fp16/v14/files
### Run
Here are some examples
``` ```
python image_from_text.py --seed=7 --text='alien life' python image_from_text.py --seed=7 --text='alien life'

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