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tencent/EVIE-Preview-4.5B · Hugging Face
Overview EVIE-Preview-4.5B is a state-of-the-art multilingual Visual Document Retrieval (VDR) model built upon Qwen3.5-4B. It employs ColBERT-style late interaction with native 128-dimensional multi-v
Overview EVIE-Preview-4.5B is a state-of-the-art multilingual Visual Document Retrieval (VDR) model built upon Qwen3.5-4B. It employs ColBERT-style late interaction with native 128-dimensional multi-vector token embeddings (4.54B parameters, BF16). By combining native GatedDeltaNet linear-attention and full-attention hybrid modeling with a compact visual projection, EVIE achieves top-tier performance across ViDoRe V1+V2 and ViDoRe V3 while generating ultra-compact 128D multi-vectors—cutting vector storage and indexing costs by 8× to 32× compared to wider 2560D–4096D representations. Key Highlights 🎯 Ultra-Compact 128D Index: Native 128-dimensional multi-vector representations drastically shrink downstream storage and index latency without sacrifice in retrieval precision. 🏆 SOTA on ViDoRe Benchmarks: Outperforms larger 8B models on ViDoRe V3 (leading 7 of 8 public domains) and delivers top average accuracy on ViDoRe V1+V2 (85.93 nDCG@5). 🌐 Robust Multilingual & Multi-Format: Strong zero-shot generalization across diverse languages (EN, FR, DE, IT, ES, PT, ZH, etc.) and visual formats (charts, tables, scientific reports, financial filings). ⚡ Seamless ColPali Compatibility: Fully integrated with the standard colpali-engine ecosystem and late-interaction scoring pipelines. submitted by /u/jacek2023 [link] [comments]
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Source: r/LocalLLaMA | 2026-08-17