Sentence Transformers is one of the most popular Language AI/NLP tools. Tens of thousands of users rely on it to build systems for text classification, neural/semantic search, text clustering, and other language AI tasks. In Episode 3 of our series on applied NLP topics, tools, and people, we take a deep dive into this important tool with Nils Reimers, our Director and Principal Scientist of Machine Learning at Cohere.

View the full episode (also embedded below). Feel free to post questions or comments in the thread on this episode in the Cohere Discord channel.

Nils is the creator of Sentence-BERT and has authored several well-known research papers, including Sentence-BERT and the popular Sentence Transformers library. He’s also worked as a Research Scientist at HuggingFace, (co-)founded several web companies, and worked as an AI consultant in the area of investment banking, media, and IoT.

In our conversation, Nils gives us an introduction to the Sentence-BERT package and the large language models provided in it. He also shares some lessons from his experience in open-source development of such a popular package. Finally, Nils touches on his research collaborations on how to evaluate embeddings through works like MTEB: Massive Text Embedding Benchmark and BEIR.

To go deeper into these tools, and other concepts around embeddings, watch the video and join the conversation on Discord. Stay tuned for more episodes in our Talking Language AI series!

Sentence Transformers and Embedding Evaluation - Talking Language AI Ep#3