TinyLLaVA-Video
Collection
A Simple Framework of Small-scale LMMs for Video Understanding.
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6 items
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Updated
Here, we introduce TinyLLaVA-Video-Phi2-Naive-16-512. For LLM and vision tower, we choose Phi-2 and siglip-so400m-patch14-384, respectively. The model adopts the Naive Video-Level Resampler, samples 16 frames from each video, and represents the video sequence using 512 tokens.
Result
| Model (HF Path) | #Frame/Query | Video-MME | MVBench | LongVideoBench | MLVU |
|---|---|---|---|---|---|
| Zhang199/TinyLLaVA-Video-Qwen2.5-3B-Group-1fps-512 | 1fps/512 | 47.7 | 47.0 | 42.0 | 52.6 |
| Zhang199/TinyLLaVA-Video-Qwen2.5-3B-Group-16-512 | 16/512 | 47.0 | 45.5 | 42.4 | 52.5 |
| Zhang199/TinyLLaVA-Video-Qwen2.5-3B-Naive-16-512 | 16/512 | 44.7 | 42.5 | 37.6 | 48.1 |
| Zhang199/TinyLLaVA-Video-Phi2-Naive-16-512 | 16/512 | 42.7 | 42.0 | 42.2 | 46.5 |
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