Hi everyone, Joshua from Hugging Face (and the creator of Transformers.js) here. Starting with embeddings, we hope to simplify and improve the developer experi

Hi everyone, Joshua from Hugging Face (and the creator of Transformers.js) here. Starting with embeddings, we hope to simplify and improve the developer experience when working with embeddings. Supabase already has great support for storage and retrieval of embeddings (thanks to pgvector) [0], so it feels like this collaboration was long overdue! Open-source embedding models are both smaller and more performant [1] than closed-source alternatives, so it's quite surprising that 98% of Supabase applications currently use OpenAI's text-embedding-ada-002 [2]. Probably because it is just easier to access? Well... that changes today! You can also iterate extremely quickly: experiment with and choose the model that works best for you (no vendor lock-in)! In fact, since the article was written, a new leader has just appeared on top of the MTEB leaderboard [3]. I look forward to answering any questions you have! [0] https://supabase.com/vector https://supabase.com/vector [1] https://huggingface.co/spaces/mteb/leaderboard https://huggingface.co/spaces/mteb/leaderboard [2] https://supabase.com/blog/hugging-face-supabase https://supabase.com/blog/hugging-face-supabase [3] https://huggingface.co/BAAI/bge-large-en https://huggingface.co/BAAI/bge-large-en