| examples | ||
| min_dalle | ||
| replicate | ||
| .gitattributes | ||
| .gitignore | ||
| image_from_text.py | ||
| LICENSE | ||
| min_dalle.ipynb | ||
| README.md | ||
| requirements.txt | ||
| setup.sh | ||
min(DALL·E)
This is a minimal implementation of Boris Dayma's DALL·E Mini in PyTorch. It has been stripped to the bare essentials necessary for doing inference. 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
The flax model, and the code for coverting it to torch, have been moved here.
Setup
Run sh setup.sh to install dependencies and download pretrained models. The torch models can be manually downloaded here.
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.
Examples
python image_from_text.py --text='artificial intelligence' --seed=7
python image_from_text.py --text='a comfy chair that looks like an avocado' --mega --seed=10
python image_from_text.py --text='court sketch of godzilla on trial' --mega --seed=40
python image_from_text.py --text='trail cam footage of gollum eating watermelon' --mega --seed=1
