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qianyu chen
2024-08-14 18:31:28 +08:00
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@@ -53,7 +53,9 @@ If your input consists of a single image, you can use a single placeholder **\<i
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#### Multiple Images Example
For inputs with multiple images, you should use a dictionary where each key represents a unique placeholder (e.g., **\<image_00\>**, **\<image_01\>**), and the corresponding value is the image path. You can then use these placeholders in the conversation to insert the images at specific positions.
For inputs containing multiple images, utilize a dictionary where each key represents a unique placeholder (e.g., \textbf{\textbackslash image\_00}, \textbf{\textbackslash image\_01}) with the corresponding image path as its value. These placeholders can then be used within the conversation to seamlessly insert images at specific positions.
Additionally, to optimize resource management, especially when dealing with large batches of images during training or inference, consider reducing \texttt{max\_slice\_nums}. If you are performing multi-image supervised fine-tuning (SFT), it's recommended to set \texttt{MODEL\_MAX\_LENGTH=4096} in your script for better performance.
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