36 lines
1.7 KiB
Markdown
36 lines
1.7 KiB
Markdown
# min(DALL·E)
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[](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`, `torch`, and `flax`. PyTorch inference with DALL·E Mega takes about 10 seconds in colab.
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### Setup
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Run `sh setup.sh` to install dependencies and download pretrained models. The `wandb` python package is installed to download DALL·E mini and DALL·E mega. Alternatively, the models can be downloaded manually here:
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[VQGan](https://huggingface.co/dalle-mini/vqgan_imagenet_f16_16384),
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[DALL·E Mini](https://wandb.ai/dalle-mini/dalle-mini/artifacts/DalleBart_model/mini-1/v0/files),
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[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 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. The colab notebook demonstrates how to load a model once and run it multiple times.
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Here are some examples:
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```
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python3 image_from_text.py --text='artificial intelligence' --torch
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```
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```
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python image_from_text.py --text='a comfy chair that looks like an avocado' --torch --mega --seed=10
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```
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```
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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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