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@@ -88,7 +88,7 @@ and is comparable with Mistral-7B-Instruct-v0.1 on MMLU and MT-Bench in English.
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  In this test, we use the first 700 characters of the [web article](https://health.udn.com/health/story/5976/7699252?from=udn_ch1005_main_index) as the input and ask the model to write the same article again.
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  All models were inferenced with `vllm` on 2 NVIDIA RTX A6000 (TP=2).
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- | Models | Inference Time (sec)|Estimated Max Input Length (TC Char)|
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  |--------------------------------------------------------------------|-------------------|--------------------------|
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  | Yi-6B | 10.62 | 5.2k |
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  | **Breeze-7B-Instruct-v0.1** | 10.74 | 11.1k |
 
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  In this test, we use the first 700 characters of the [web article](https://health.udn.com/health/story/5976/7699252?from=udn_ch1005_main_index) as the input and ask the model to write the same article again.
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  All models were inferenced with `vllm` on 2 NVIDIA RTX A6000 (TP=2).
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+ | Models | Inference Time (sec)|Estimated Max Input Length (Char)|
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  |--------------------------------------------------------------------|-------------------|--------------------------|
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  | Yi-6B | 10.62 | 5.2k |
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  | **Breeze-7B-Instruct-v0.1** | 10.74 | 11.1k |