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shi-labs/pretrain_dsg_OLA-VLM-CLIP-ConvNeXT-Phi3-4k-mini
pretrain_dsg_OLA-VLM-CLIP-ConvNeXT-Phi3-4k-mini is a image-text-to-text model from shi-labs. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
Note: This is the pretrained model used for OLA-VLM-CLIP-ConvNeXT-Phi3-4k-mini.
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BF164.7B · 97%
From the Hugging Face model README
Note: This is the pretrained model used for OLA-VLM-CLIP-ConvNeXT-Phi3-4k-mini.
OLA-VLM distills target visual information into the intermediate representations of the LLM from a set of target encoders. It adopts a predictive embedding optimization approach at selected LLM layers during training to minimize the embedding losses along with the next token prediction (NTP) objective, resulting in a vision-centric approach to training the Multimodal Large Language Model.
If you found our work useful in your research, please consider starring ⭐ us on GitHub and citing 📚 us in your research!
@article{jain2024ola_vlm,
title={{OLA-VLM: Elevating Visual Perception in Multimodal LLMs with Auxiliary Embedding Distillation}},
author={Jitesh Jain and Zhengyuan Yang and Humphrey Shi and Jianfeng Gao and Jianwei Yang},
journal={arXiv},
year={2024}
}