seongminp/transformers-into-vaes
Code for "Finetuning Pretrained Transformers into Variational Autoencoders"
This project helps researchers and practitioners in natural language processing (NLP) adapt large, pre-trained language models for tasks requiring text generation and latent space manipulation. It takes an existing Transformer model and text datasets, and outputs a fine-tuned Variational Autoencoder (VAE) capable of generating diverse and coherent text. This is designed for NLP researchers and machine learning engineers working on advanced text generation and understanding.
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Use this if you need to transform a pre-trained Transformer model into a Variational Autoencoder for tasks like controlled text generation or learning meaningful latent representations of text.
Not ideal if you are looking for a simple, off-the-shelf text generation tool without delving into model architecture fine-tuning.
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Python
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Last pushed
May 26, 2022
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