A Fast and Stable GAN for Small and High Resolution Imagesets
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This model costs approximately $0.00027 to run on Replicate, or 3703 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.
This model runs on CPU hardware. Predictions typically complete within 3 seconds. The predict time for this model varies significantly based on the inputs.
The official pytorch implementation of the paper “Towards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesis”, the paper can be found here.
Instructions for how to retrain FastGAN on your own dataset can be found in the GitHub README.
