Text Embeddings and Semantic Search with Transformer Models

Learn how Transformer models can be used to represent documents and queries as vectors called embeddings. In this video, we apply this technique to create a semantic search engine! This video is part of the Hugging Face course: http://huggingface.co/course Open in colab to run the code samples: https://colab.research.google.com/github/huggingface/notebooks/blob/master/course/videos/semantic_search.ipynb Related videos: - Loading a custom dataset — https://youtu.be/HyQgpJTkRdE - Slide and dice a dataset 🔪 — https://youtu.be/tqfSFcPMgOI Don't have a Hugging Face account? Join now: http://huggingface.co/join Have a question? Checkout the forums: https://discuss.huggingface.co/c/course/20 Subscribe to our newsletter: https://huggingface.curated.co/