Low Dim Embeddings from Similarity Transformer Models
I’m looking for a  similarity model which may be capable of creating low dimensional embeddings for data of approximately 50 thousands of sentences. Right now I’m using paraphrase-MiniLM-L3-v2 model, which outputs vectors of dim 384. This is just too much for my objective. I was wondering if there was a good model which would output embeddings of dim around 100, or less…If there’s none, does anyone know if dim reduction techniques like PCA lose too much information? Any recommendations for a dim reduction technique?
2024-04-05T11:09:03Z
what models can i find on hf that has a low dim embedding like 50-100please paste the linksz below