Pythia vs Terracotta

Pythia is an extensive suite designed to analyze the development and scaling of large language models (LLMs). It comprises 16 models, each trained with public data in a consistent order, featuring sizes ranging from 70 million to 12 billion parameters. The project provides public access to 154 checkpoints per model, as well as tools to reproduce training data loaders for in-depth research. Pythia aims to aid various research domains with case studies on topics like memorization, the impact of term frequency on few-shot learning, and strategies for mitigating gender bias. This carefully controlled environment offers unique insights into the training dynamics of LLMs. The suite includes trained models, analysis code, training code, and data, all accessible via its GitHub repository.

Terracotta is a cutting-edge platform designed to enhance the workflow for developers and researchers working with large language models (LLMs). This intuitive and user-friendly platform allows you to manage, iterate, and evaluate your fine-tuned models with ease. With Terracotta, you can securely upload data, fine-tune models for various tasks like classification and text generation, and create comprehensive evaluations to compare model performance using both qualitative and quantitative metrics. Our tool supports connections to major providers like OpenAI and Cohere, ensuring you have access to a broad range of LLM capabilities. Terracotta is the creation of Beri Kohen and Lucas Pauker, AI enthusiasts and Stanford graduates, who are dedicated to advancing LLM development. Join our email list to stay informed on the latest updates and features that Terracotta has to offer.