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Vision Encoder - DinoV2 + SigLIP @384px resolution. Why 2 vision encoders? Connector - MLP (Dino and SigLIP features are concatenated and then projected to Phi3 representation space) Language Model - Phi3 + LoRA...
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1 sourceVerified Aug 28
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2 excerpts--- datasets: - liuhaotian/LLaVA-Instruct-150K - liuhaotian/LLaVA-CC3M-Pretrain-595K language: - en metrics: - accuracy pipeline_tag: visual-question-answering --- # DinoV2-SigLIP-Phi3(LoRA) VLM * **Vision Encoder** - DinoV2 + SigLIP @384px resolution. [Why 2 vision encoders?](https://arxiv.org/abs/2401.06209) * **Connector** - MLP (Dino and SigLIP features are concatenated and then projected to Phi3 representation space) * **Language Model** - Phi3 + LoRA * **Pre-train (Align) Dataset** - LLaVA-CC3M-Pretrain-595K * **Fine-tune (Instruction) Dataset** - LLAVA-v1.5-Instruct + LRV-Instruct 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).
Scripts to build and train the models are available at NMS05/DinoV2-SigLIP-Phi3-LoRA-VLM.
Source context: 0 downloads · 0 likes · Pipeline visual-question-answering · Repo nms05/Dinov2-SigLIP-Phi3-LoRA
