Perplexity releases pplx-embed-v2-late 0.6B and 9B models
Both models, distilled from an 18B teacher, share an embedding space so the 9B can index and the 0.6B can query.
3 stories, newest first · one card per story
Both models, distilled from an 18B teacher, share an embedding space so the 9B can index and the 0.6B can query.
GLIE compresses visual document retrieval embeddings to four vectors per page while retaining nearly 80% of uncompressed nDCG@5 accuracy.
Hugging Face details building and using multi-vector late-interaction embedding models with Sentence Transformers for retrieval workloads.
Today 1.6K readers · 2.5K views · 780 reads · all time 189K views