An omni model accepting and generating various types of inputs and outputs, including text, audio, images, and video.

A multimodal model that combines text and vision capabilities, allowing users to instruct it to analyze image inputs.

A multimodal transformer model pre-trained to predict the next token in a document, which can accept image and text inputs and produce text outputs.

An interactive model designed to engage in conversations, built on top of GPT 3.5.

Fine-tuned GPT using supervised learning (instruction tuning) and reinforcement learning from human feedback to align with user intent.

A fine-tuned GPT-3 model utilizing text-based web browsing, trained via imitation learning and human feedback, enhancing its ability to answer long-form questions with factual accuracy.

A GPT language model finetuned on publicly available code from GitHub.

Demonstrates that scaling up language models greatly improves task-agnostic, few-shot performance.

Demonstrates that language models begin to learn various language processing tasks without any explicit supervision.

A Decoder only transformer which is autoregressively pretrained and then finetuned for specific downstream tasks using task-aware input transformations.