Granite Embedding 发布了新的多语言 R2 模型
Granite Embedding发布了新的多语言嵌入模型R2，该模型参数量为97M，但在MTEB多语言检索任务中表现优于其他参数量低于100M的模型。
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证据
- HHugging Face Blog公司披露2026-05-15 02:55
> Enterprise-Ready by Design A Strong Sub-100M Multilingual Model What Changed from R1 Training the Full-Size 311M Model Building the compact 97M Multilingual model Benchmark Results Multilingual Retrieval Speed and Throughput Matryoshka Embeddings (311M) Cross-lingual Retrieval…
- HHugging Face Blog公司披露2026-05-15 02:55
Try The Models TL;DR: Two new Apache 2.0 multilingual embedding models built on ModernBERT — a 97M-parameter compact model that beats every open sub-100M multilingual embedder on MTEB Multilingual Retrieval (60.3), and a 311M full-size model that scores 65.2 on MTEB Multilingual…
- HHugging Face Blog公司披露2026-05-15 02:55
Try The Models TL;DR: Two new Apache 2.0 multilingual embedding models built on ModernBERT — a 97M-parameter compact model that beats every open sub-100M multilingual embedder on MTEB Multilingual Retrieval (60.3), and a 311M full-size model that scores 65.2 on MTEB Multilingual…