Google Gemini Embedding 2: Multimodal AI Breakthrough | Bhavini Kapoor posted on the topic | LinkedIn
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ibm.com
The Llama-Embed-Nemotron-8B text embedding model now ranks as the top open and portable model on the Hugging Face MMTEB leaderboard. Why it’s leading the race: ✅ Strong performance for retrieval, reranking, classification, and bi‑text mining ✅ Effectively handles retrieval in low-resource languages and cross-lingual setups ✅ Trained on 16M query‑document pairs (8M public 8M synthetic) ✅ Combines model merging and refined hard‑negative mining for better accuracy Leaderboard 🏆 https://huggingface
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The Llama-Embed-Nemotron-8B text embedding model now ranks as the top open and portable model on the Hugging Face MMTEB leaderboard. Why it’s leading the race: ✅ Strong performance for retrieval, reranking, classification, and bi‑text mining ✅ Effectively handles retrieval in low-resource languages and cross-lingual setups ✅ Trained on 16M query‑document pairs (8M public 8M synthetic) ✅ Combines model merging and refined hard‑negative mining for better accuracy Leaderboard 🏆 https://huggingface
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Last week, we made Gemini Embedding 2, our first natively multimodal embedding model, available to the general public. Since then, developers have used it to build video analysis tools, visual shopping assistants, and more.But you might be wondering... what is an embedding model? 🤔 Let’s break it down! 1. What is it?Think of an embedding model as a "universal translator." It takes text, images, video, and audio data and turns them into a long string of numbers, like a unique digital fingerprint
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