About DeepMind RETRO

DeepMind RETRO is an innovative tool that enhances the capabilities of auto-regressive language models. It achieves this by conditioning on document chunks retrieved from a vast corpus, based on local similarity with preceding tokens.

Here are four key features of DeepMind RETRO

  1. Large Corpus: RETRO operates on a massive database of 2 trillion tokens, enabling it to retrieve relevant document chunks for conditioning.
  2. Efficient Performance: Despite using 25 times fewer parameters, RETRO delivers performance comparable to GPT-3 and Jurassic-1 on the Pile.
  3. Fine-Tuning Capabilities: After fine-tuning, RETRO’s performance translates to downstream knowledge-intensive tasks such as question answering.
  4. Developer-Friendly: RETRO is an excellent alternative for developers looking for large language models (LLMs) and can be integrated into various applications