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Ask HN: Best Embedding Models?

18 points by devstein 2 months ago · 19 comments · 1 min read


Hey HN, which embedding models are people using? There has been so much development around foundational LLMs, but haven't seen much news about embedding models.

PhilippGille 2 months ago

Benchmarks only paint part of the picture, but it's still a decent place to start looking into recent models:

https://huggingface.co/spaces/mteb/leaderboard

rapatel0 2 months ago

I've liked qwen and embeddinggemma for local search. Qwen because 32K is enough to basically fit a whole page into the context window and embeddiggemma because it's crazy efficient.

stevenfazzio 2 months ago

Cohere's embed-v4.0 is my daily driver as far as a high performance model is concerned. I do a lot of cluster analysis and data visualization and I like that there's an `input_type="clustering"` mode in addition to the standard `input_type="search"` mode.

For a fast, open, and local model, I've found it hard to beat https://huggingface.co/sentence-transformers/all-MiniLM-L6-v...

emschwartz 2 months ago

I’ve been using MixedBread, which is a pretty old model at this point. Recently, I tried comparing it to some newer models and was disappointed that the results weren’t dramatically and uniformly better.

You probably can’t go wrong if you pick a recent one that scores decently well on benchmarks and is at the right price point (or memory requirement) for whatever you’re trying to do.

pstorm 2 months ago

Just fyi, for RAG/similarity search, adding a reranker was much bigger pay off than switching embedding models.

  • devsteinOP 2 months ago

    What top K do you use for vector search before passing into the reranker?

    • pstorm 2 months ago

      At a minimum, you increase top-k to cast a wider net, then after reranking, take the N you really want. You have to play around with it a bit, but that’s the idea.

sp1982 2 months ago

I am using openai small embedding model with custom compression. It is super cheap. You can read more at https://corvi.careers/blog/vector-search-embedding-compressi...

LogicCraft678 2 months ago

Feels like embeddings are underrated compared to LLM's hype, but they doing great.

  • Alifatisk 2 months ago

    Why do you feel like embeddings are underrated? What is it with embeddings that deserves more attention?

preetsojitra 2 months ago

Meta's Perception Encoder Audio-Visual, its CLIP like but has three modality: Audio, Video and Text

didgeoridoo 2 months ago

I’m partial to jina.ai — they have open models for code and prose, all easily runnable locally.

jayshah5696 2 months ago

embeddings are easy to fine tune. Try modern bert.

mutant 2 months ago

not a single "of what data" or "in what env"

best in what?

sovenyr 2 months ago

please check OpenAI embedding models - especially small one

Yogeshshirsath 2 months ago

E5 (Microsoft)

frederickabrah 2 months ago

who knows a tool for rug check in crypto

halvorbuilds 2 months ago

gemma4

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