1.9 KiB
Vendored
1.9 KiB
Vendored
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.
Install
$ pip install min-dalle
Usage
Use the python script image_from_text.py to generate images from the command line.
$ python image_from_text.py --text='artificial intelligence' --seed=7
$ python image_from_text.py --text='court sketch of godzilla on trial' --mega
To load a model once and generate multiple times, first initialize MinDalleTorch
from min_dalle import MinDalleTorch
model = MinDalleTorch(
is_mega=True,
is_reusable=True,
models_root='./pretrained'
)
The required models will be downloaded to models_root if they are not already there. After the model has loaded, call generate_image with some text and a seed as many times as you want.
image = model.generate_image("a comfy chair that looks like an avocado")
display(image)
image = model.generate_image(
"trail cam footage of gollum eating watermelon",
seed=1
)
display(image)
