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SliMM-DeepStackE-Qwen2VL-2B

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Transformers
Safetensors
qwen2_vl
text-generation
multimodal
conversational
text-generation-inference
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  |----------------------------------------------------------|------------|----------------|-------------|-------------|
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  |Qwen2VL-2B (official evaluation) |41.1 | 73.5 |74.7 |90.1 |
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  |Qwen2VL-2B (our evaluation, 1024 max vistokens to LLM) |39.4 | 75.6 |70.7 |90.4 |
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- |SliMM-DeepStackE-Qwen2VL-0.5B (320 max vistokens to LLM) |40.7 | 74.5 |74.7 |85.4 |
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  |SliMM-DeepStackE-Qwen2VL-0.5B (400 max vistokens to LLM) |41.2 | 76.8 |74.9 |88.0 |
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  ## 🔗 Citation
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  If you find our work helpful, please consider citing our paper :paperclip: and starring our repo :star2: :
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  |----------------------------------------------------------|------------|----------------|-------------|-------------|
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  |Qwen2VL-2B (official evaluation) |41.1 | 73.5 |74.7 |90.1 |
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  |Qwen2VL-2B (our evaluation, 1024 max vistokens to LLM) |39.4 | 75.6 |70.7 |90.4 |
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+ |SliMM-DeepStackE-Qwen2VL-0.5B (256 max vistokens to LLM) |40.7 | 74.5 |74.7 |85.4 |
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  |SliMM-DeepStackE-Qwen2VL-0.5B (400 max vistokens to LLM) |41.2 | 76.8 |74.9 |88.0 |
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+ <p align="left">
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+ <img src="https://cdn-uploads.huggingface.co/production/uploads/64d852a4bab152b2470bf96e/dtVzPkcIp40oH8sg7MG_u.png" alt="Trade-off between N Vistokens for LLM and Acc" style="width:500px;" > <br>
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+ </p>
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  ## 🔗 Citation
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  If you find our work helpful, please consider citing our paper :paperclip: and starring our repo :star2: :
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