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@@ -322,6 +322,21 @@ code_embeddings = model.encode(
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  ```
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  </details>
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  ## Jina-VDR
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  Alongside `jina-embeddings-v4`, we’re releasing [Jina VDR](https://github.com/jina-ai/jina-vdr), a multilingual, multi-domain benchmark for visual document retrieval. The task collection can be viewed [here](https://huggingface.co/collections/jinaai/jinavdr-visual-document-retrieval-684831c022c53b21c313b449), and evaluation instructions can be found [here](https://github.com/jina-ai/jina-vdr).
 
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  ```
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  </details>
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+ <details>
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+ <summary>via <a href="https://github.com/vllm-project/vllm">vLLM</a></summary>
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+ We provide separate model versions for each task (`retrieval`, `text-matching`, `code`) where specific adapter is merged into the base `Qwen2.5-VL` weights.
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+ This modification enables native compatibility with vLLM.
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+ Instructions and usage examples for each task are available in their respective directories:
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+ - [jina-embeddings-v4-vllm-retrieval](https://huggingface.co/jinaai/jina-embeddings-v4-vllm-retrieval)
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+ - [jina-embeddings-v4-vllm-text-matching](https://huggingface.co/jinaai/jina-embeddings-v4-vllm-text-matching)
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+ - [jina-embeddings-v4-vllm-code](https://huggingface.co/jinaai/jina-embeddings-v4-vllm-code)
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+ Please refer to the directory that matches your task for more details.
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+ </details>
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  ## Jina-VDR
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  Alongside `jina-embeddings-v4`, we’re releasing [Jina VDR](https://github.com/jina-ai/jina-vdr), a multilingual, multi-domain benchmark for visual document retrieval. The task collection can be viewed [here](https://huggingface.co/collections/jinaai/jinavdr-visual-document-retrieval-684831c022c53b21c313b449), and evaluation instructions can be found [here](https://github.com/jina-ai/jina-vdr).