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Models

Foundation, generative, multimodal and specialised models.

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2023

2022

2021

  • Jul 15, 2021 RoseTTAFold

    RoseTTAFold is a three-track neural network for protein structure prediction, published by the Baker lab in 2021; its accuracy approached AlphaFold2's at CASP14, it models protein–protein complexes from sequence alone, and it is distributed as open code with a public web server.

    Research historyOpen sourceDeep learning

  • Jun 2021 GPT-J-6B

    GPT-J-6B is a six-billion-parameter open language model released by EleutherAI in June 2021 under the Apache 2.0 license. Its published scores sit close to GPT-3 Curie, making it a widely used free baseline for large-model research.

    Large language modelsResearch historyOpen source

  • Mar 21, 2021 GPT-Neo

    GPT-Neo is a family of open text-generation models released by EleutherAI in March 2021 at 125M, 1.3B and 2.7B parameters, built to replicate the GPT-3 architecture and distributed with freely downloadable weights under an MIT license.

    Large language modelsResearch historyOpen source

  • Jan 5, 2021 CLIP

    An image-text model from OpenAI that learns to match pictures with their captions. Trained on about 400 million image-caption pairs, it can classify images by comparing them against written prompts, with no task-specific training.

    Open sourceFoundation modelsMultimodal

2019

2018

  • Oct 11, 2018 BERT

    BERT is a language model from Google that reads text in both directions and is pre-trained by filling in masked words. Fine-tuned per task, it set new records on question answering and language-understanding benchmarks and later went into Google Search.

    Large language modelsResearch historyOpen source

  • Jun 11, 2018 GPT-1

    GPT-1 was OpenAI's first generative pre-trained transformer, published in June 2018. It showed that one language model, pre-trained on unlabelled text and then fine-tuned, could improve results on many language tasks.

    Large language modelsResearch historyOpen source