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@@ -86,7 +86,7 @@ and is comparable with Mistral-7B-Instruct-v0.1 on MMLU and MT-Bench in English.
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  ## Inference Performance
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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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  ## Inference Performance
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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 inferences run on 2 RTX A6000 GPUs (using `vllm`, with a tensor-parallel size of 2).
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  | Models | Inference Time (sec)|Estimated Max Input Length (Char)|
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  |--------------------------------------------------------------------|-------------------|--------------------------|