A New Approach to Synthetic Text Generation
This demo is a practical example of the geometric approach to latent space sampling as described in the paper Navigating the Geometry of Language: A New Approach to Synthetic Text Generation. It allows you to generate new synthetic data given some reference text using OpenAI’s ada-002 embedding model. You can browse the live demo here.
This demo requires PyTorch to be compiled with CUDA support.
pip install -r requirements.txt
OPENAI_API_KEY=<KEY> OPENAI_ORGANIZATION=<ORG> streamlit run streamlit_app.py