Download
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
License
MIT LicenseFollow Minimal text diffusion
Other Useful Business Software
Enterprise-grade ITSM, for every business
Freshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of Minimal text diffusion!
