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Jo Kristian Bergum

Chief Scientist at Vespa.ai

I'm looking at the MTEB leaderboard this AM. Amazingly, mxbai-embed-large-v1 ranks at 12 despite its small size relative to the other Billion-sized parameters models. In addition to strong performance for a relatively small size, it comes with MRL and BQL flexibility, which can slash cost of storing and searching the embedding representations (with a slight degradation in accuracy) https://lnkd.in/d5jq9a2R

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Tom Aarsen

🤗 Sentence Transformers, SetFit & NLTK maintainer, MLE @ Hugging Face

4mo

Luckily, you can now filter by model size 😄

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Nicolaj Søndergaard Mühlbach

Sr. Machine Learning Scientist | PhD, Postdoc in econometrics, machine learning, and NLP

4mo

Giovanni Rizzi this is the model I was showing you

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Shubham Pawar

LLM Research Lead @ Qloo | Redefining Cultural Taste with LLMs

4mo

mixedbread.ai models are great! 👏❤️

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🎯Renato Ghica🎯

Trusted Technology Advisor | AI/ML Innovator Driving FinTech Transformation | Expertise in Finance, Banking, Capital Markets, Wealth & Risk Management | ex SVB, JPM, Citi, BofA

4mo

Good stuff. 👀 Also, I haven't ran a T-test on this particular set of data, but I would guess that these 11 LLMs have scores that are not statistically significant from each other, at the 95% or even 90% 2-talied confidence level. ❓ What do you think, Jo Kristian Bergum

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