Training and Finetuning Multimodal Embedding & Reranker Models with Sentence Transformers
Apr 16, 2026
Summary
This post introduces the Qwen/Qwen3-VL-Embedding-2B model, a 2B parameter multimodal model for sentence similarity, to the existing support for training and fine-tuning Sentence Transformers models. It highlights the model's capabilities and availability on the Hugging Face Hub.
More from the Sentence Transformers for Playlist Generation trail
- NeoMME: an efficient Multimodal-native and Multilingual Encoder
- MTEB: Massive Text Embedding Benchmark
- Introducing OlmoEarth embeddings: Custom embedding exports from OlmoEarth Studio for downstream analysis
- Build a Domain-Specific Embedding Model in Under a Day
- Granite Embedding Multilingual R2: Open Apache 2.0 Multilingual Embeddings with 32K Context — Best Sub-100M Retrieval Quality