Visual Question Answering
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+ ---
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+ datasets:
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+ - liuhaotian/LLaVA-Instruct-150K
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+ - liuhaotian/LLaVA-CC3M-Pretrain-595K
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+ language:
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+ - en
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+ metrics:
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+ - accuracy
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+ pipeline_tag: visual-question-answering
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+ ---
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+ # DinoV2-SigLIP-Phi3(LoRA) VLM
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+
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+ * **Vision Encoder** - DinoV2 + SigLIP @384px resolution. [Why 2 vision encoders?](https://arxiv.org/abs/2401.06209)
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+ * **Connector** - MLP (Dino and SigLIP features are concatenated and then projected to Phi3 representation space)
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+ * **Language Model** - Phi3 + LoRA
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+ * **Pre-train (Align) Dataset** - LLaVA-CC3M-Pretrain-595K
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+ * **Fine-tune (Instruction) Dataset** - LLAVA-v1.5-Instruct + LRV-Instruct
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+
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+ Scripts to build and train the models are available at [NMS05/DinoV2-SigLIP-Phi3-LoRA-VLM](https://github.com/NMS05/DinoV2-SigLIP-Phi3-LoRA-VLM).