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llava-v1.5-13b-xtuner

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@@ -32,7 +32,7 @@ pip install -U 'xtuner[deepspeed]'
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  ```shell
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  xtuner chat lmsys/vicuna-13b-v1.5 \
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- --visual-encoder openai/clip-vit-large-patch14 \
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  --llava xtuner/llava-v1.5-13b-xtuner \
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  --prompt-template vicuna \
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  --image $IMAGE_PATH
@@ -59,7 +59,7 @@ XTuner integrates the MMBench evaluation, and you can perform evaluations with t
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  ```bash
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  xtuner mmbench lmsys/vicuna-13b-v1.5 \
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- --visual-encoder openai/clip-vit-large-patch14 \
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  --llava xtuner/llava-v1.5-13b-xtuner \
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  --prompt-template vicuna \
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  --data-path $MMBENCH_DATA_PATH \
 
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  ```shell
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  xtuner chat lmsys/vicuna-13b-v1.5 \
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+ --visual-encoder openai/clip-vit-large-patch14-336 \
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  --llava xtuner/llava-v1.5-13b-xtuner \
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  --prompt-template vicuna \
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  --image $IMAGE_PATH
 
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  ```bash
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  xtuner mmbench lmsys/vicuna-13b-v1.5 \
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+ --visual-encoder openai/clip-vit-large-patch14-336 \
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  --llava xtuner/llava-v1.5-13b-xtuner \
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  --prompt-template vicuna \
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  --data-path $MMBENCH_DATA_PATH \