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andre-z

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1 ポイント·投稿者 andre-z·昨年·0 コメント

コメント

andre-z
·6 か月前·議論
What do I say? Happy to talk about "fakes". Here is my calendar. Feel free to book a slot. https://qdrant.to/andre-z
andre-z
·8 か月前·議論
FAISS is not suitable for production. The dedicated vector search solutions solve all the issues you mentioned: you just store the metadata along with vectors in JSON format. At least, with Qdrant, it works like this: https://qdrant.tech/documentation/concepts/payload/
andre-z
·昨年·議論
miniCOIL is a contextualized per-word embedding model. It generates extremely small embeddings (8dim or even 4dim) while still preserving the word's context for each word in a sentence.

GitHub https://github.com/qdrant/miniCOIL HuggingFace https://huggingface.co/Qdrant/minicoil-v1
andre-z
·昨年·議論
"Slowness can arise from a misconfigured index or if filterable attributes aren't listed." ;)
andre-z
·昨年·議論
Qdrant runs on Linux/Mac/Windows and on x86/ARM processors