minimal text diffusion

We have hosted the application minimal text diffusion in order to run this application in our online workstations with Wine or directly.

Quick description about minimal text diffusion:

A minimal implementation of diffusion models of text: learns a diffusion model of a given text corpus, allowing to generate text samples from the learned model. The main idea was to retain just enough code to allow training a simple diffusion model and generating samples, remove image-related terms, and make it easier to use. To train a model, run scripts/train.sh. By default, this will train a model on the simple corpus. However, you can change this to any text file using the --train_data argument. Note that you may have to increase the sequence length (--seq_len) if your corpus is longer than the simple corpus. The other default arguments are set to match the best setting I found for the simple corpus.

Features:

• Training from scratch on the greetings dataset
• Experiments with using pre-trained models and embeddings
• Controllable Generation
• A minimal implementation of diffusion models of text
• Generate text samples from the learned model
• Opportunities for further minimization

Programming Language: Python.
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