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README.md
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@@ -68,13 +68,15 @@ InternVL 2.0 is a multimodal large language model series, featuring models of va
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### Video Benchmarks
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- We evaluate our models on MVBench by extracting 16 frames from each video, and each frame was resized to a 448x448 image.
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### 视频相关评测
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- 我们通过从每个视频中提取16帧来评估我们的模型在MVBench上的性能，每个视频帧被调整为448x448的图像。
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### Video Benchmarks
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| Benchmark | GPT-4V | VILA-1.5 | LLaVA-NeXT-Video | InternVL-Chat-V1-5 | InternVL2-26B |
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| :-------------------------: | :----: | :------: | :--------------: | :----------------: | :-----------: |
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| Model Size | - | 34B | 34B | 25.5B | 25.5B |
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| MVBench | - | - | - | 52.1 | 67.5 |
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| MMBench-Video<sub>8f</sub> | 1.53 | - | - | 1.26 | 1.27 |
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| MMBench-Video<sub>16f</sub> | 1.68 | - | - | 1.31 | 1.41 |
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| Video-MME<br>wo subs | 59.9 | 59.0 | 52.0 | TODO | TODO |
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| Video-MME<br>w/ subs | 63.3 | 59.4 | 54.9 | TODO | TODO |
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- We evaluate our models on MVBench by extracting 16 frames from each video, and each frame was resized to a 448x448 image.
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### 视频相关评测
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| 评测数据集 | GPT-4V | VILA-1.5 | LLaVA-NeXT-Video | InternVL-Chat-V1-5 | InternVL2-26B |
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| :-------------------------: | :----: | :------: | :--------------: | :----------------: | :-----------: |
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| 模型大小 | - | 34B | 34B | 25.5B | 25.5B |
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| MVBench | - | - | - | 52.1 | 67.5 |
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| MMBench-Video<sub>8f</sub> | 1.53 | - | - | 1.26 | 1.27 |
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| MMBench-Video<sub>16f</sub> | 1.68 | - | - | 1.31 | 1.41 |
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| Video-MME<br>wo subs | 59.9 | 59.0 | 52.0 | TODO | TODO |
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| Video-MME<br>w/ subs | 63.3 | 59.4 | 54.9 | TODO | TODO |
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- 我们通过从每个视频中提取16帧来评估我们的模型在MVBench上的性能，每个视频帧被调整为448x448的图像。
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