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# MonoQwen2-VL-v0.1
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## Model Overview
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The **MonoQwen2-VL-v0.1** is a LoRA
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That is, given a couple of image and query fed into the prompt of the VLM, the model is tasked to generate "True" if the image is relevant to the query and "False" otherwise.
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During inference, a relevancy score can then be obtained by comparing the logits of the two tokens and this score can effectively be used to rerank the candidates generated by a first-stage retriever (such as DSE or ColPali) or filter them using a threshold.
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# MonoQwen2-VL-v0.1
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## Model Overview
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The **MonoQwen2-VL-v0.1** is a multimodal reranker finetuned with LoRA from [Qwen2-VL-2B](https://huggingface.co/Qwen/Qwen2-VL-2B-Instruct), optimized for asserting pointwise image-query relevance using the [MonoT5](https://arxiv.org/pdf/2101.05667) objective.
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That is, given a couple of image and query fed into the prompt of the VLM, the model is tasked to generate "True" if the image is relevant to the query and "False" otherwise.
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During inference, a relevancy score can then be obtained by comparing the logits of the two tokens and this score can effectively be used to rerank the candidates generated by a first-stage retriever (such as DSE or ColPali) or filter them using a threshold.
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