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In-progress implementation of GEN-CLIP

Python 1.78% Jupyter Notebook 98.22%

my-gen-clip's Introduction

my-gen-clip

In-progress implementation of GEN-CLIP. Most work was done on the taming-transformers/taming/models/clip_transfomer.py script

Installation

Create a conda enviroment based on environment.yaml file

cd taming-transformers

conda env create --file environment.yml

conda activate vqgen

Training

The basic training goes like this (futher instructions in the taming-transformers repo README)

python main.py --base configs/ffhq_thumbnails_transformer.yaml -t True --gpus 0,

The config file I used to train the first stage is configs/custom_vqgan.yaml For the second stage, I used configs/ffhq_thumbnails_transformer.yaml

Please note that training with those configurations requires the ffhq-thumbnails dataset, which is not included in this repo. You can use other datasets, further instructions can be found at

https://github.com/CompVis/taming-transformers#training-on-custom-data

For use with pretrained models, change the ckpt properties in the configuration files

Usage

To generate images from text, check the script sample_clip.py as a starting point

Weights

I don't have the resources to train for long at the moment, so unfortunately no weights are provided

my-gen-clip's People

Contributors

ryudrigo avatar

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