zhjgao/difformer
The official codebase for "Empowering Diffusion Models on the Embedding Space for Text Generation" (NAACL 2024)
This project helps machine learning engineers and researchers generate human-like text by training diffusion models on existing text data. It takes raw text datasets, preprocesses them, and then outputs a trained model capable of generating new text for tasks like translation or question paraphrasing. This tool is for those building and experimenting with advanced natural language generation systems.
No commits in the last 6 months.
Use this if you are a machine learning engineer or researcher focused on developing and evaluating state-of-the-art text generation models, particularly those leveraging diffusion techniques.
Not ideal if you need an out-of-the-box text generation solution without extensive machine learning development or model training.
Stars
56
Forks
7
Language
Python
License
MIT
Category
Last pushed
Apr 23, 2024
Commits (30d)
0
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