embedding-models
3 articles tagged with embedding-models
Microsoft open-sources Harrier embedding model with 27B parameters, 131K context window
Microsoft's Bing team has open-sourced Harrier, a 27-billion-parameter embedding model that supports over 100 languages and features a 131,072-token context window. The model ranks first on the MTEB v2 multilingual benchmark, outperforming proprietary offerings from OpenAI and Amazon, and is available on Hugging Face under the MIT license.
Microsoft releases Harrier embedding models with 32K context window, achieving 74.3 on MTEB v2
Microsoft released the Harrier-OSS embedding model family, comprising three variants with 270M, 600M, and 27B parameters. The largest model achieves 74.3 on the Multilingual MTEB v2 benchmark. All models support 32,768 max tokens and multilingual inputs across 40+ languages.
Perplexity open-sources embedding models matching Google and Alibaba with lower memory requirements
Perplexity has open-sourced two text embedding models designed to match or exceed the performance of Google's and Alibaba's embeddings while requiring significantly less memory. The move brings competitive embedding technology into the open-source ecosystem.