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

Project Samples

Minimal text diffusion Screenshot 1

Project Activity

See All Activity >

Categories

AI Text Generators, Generative AI

License

MIT License

Follow Minimal text diffusion

Minimal text diffusion Web Site

Other Useful Business Software
$300 Free Credits to Build on Google Cloud Icon
$300 Free Credits to Build on Google Cloud

New customers can spin up VMs, build with AI, and query data at no cost.

Put your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
Start Free
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of Minimal text diffusion!

Additional Project Details

Programming Language

Python

Related Categories

Python AI Text Generators, Python Generative AI

Registered

2023-03-23
Report inappropriate content