Sentence Transformers models
All 5 Sentence Transformers models on OpenDunes, priced in Algerian Dinars.
5 models
Send All-mpnet-base-v2 a sentence or a short passage and it returns a fingerprint of what the text means, so a search can find text that says the same thing in different words. Use it for finding documents, grouping similar texts, scoring closeness and ranking. Its makers rate it the best quality among their general models, and the smaller all-MiniLM-L6-v2 is about five times faster.
Send All-MiniLM-L6-v2 a sentence or a short passage and it returns a fingerprint of what the text means, so a search can find text that says the same thing in different words. You store the fingerprints and compare them for search, grouping similar texts and ranking. Its makers describe it as about five times faster than all-mpnet-base-v2, with good quality.
Send All-MiniLM-L12-v2 a sentence or a short passage and it returns a fingerprint of what the text means, so a search can find text that says the same thing in different words. Use it for semantic search, grouping similar texts and scoring how close two texts are. Its sources give it the same uses as all-MiniLM-L6-v2, so test both on a sample of your own texts.
Multi-qa-mpnet-base-dot-v1 turns questions and passages into fingerprints of their meaning, so a question finds the paragraph that answers it. It was trained on about 215 million question and answer pairs, takes inputs of up to about half a page, and its makers advise comparing fingerprints with a dot product. Pick it for question-answering search. For general similarity or grouping, use all-mpnet-base-v2.
Send Paraphrase-MiniLM-L6-v2 a sentence or a short passage and it returns a fingerprint of what the text means. Its strength is spotting paraphrases, two sentences that say the same thing in different words, which helps in finding duplicates, scoring closeness and grouping. It is small and light.