example_chat.py does not support multi-images as input?

Thank you for the favorable work! [Inference on Multiple GPUs](https://github.com/InternLM/InternLM-XComposer?tab=readme-ov-file#inference-on-multiple-gpus) in README calls [example_chat.py](https://github.com/InternLM/InternLM-XComposer/blob/main/examples/example_chat.py), but it seems like the code does not support multi-images as input. When I organize 2 images like [Data preparation in finetune guidance](https://github.com/InternLM/InternLM-XComposer/blob/main/finetune/README.md#data-preparation), an error occurs:
```
File "/playground/InternLM-XComposer/examples/example_chat.py", line 38, in
response, _ = model.chat(tokenizer, query=text, image=image, history=[], do_sample=False)
File "/root/miniconda3/envs/intern_clean/lib/python3.9/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "/root/.cache/huggingface/modules/transformers_modules/internlm/internlm-xcomposer2-vl-7b/a52d70f582fa5773dd7b297f3e1a4caf149dcf59/modeling_internlm_xcomposer2.py", line 500, in chat
image = self.encode_img(image)
File "/root/.cache/huggingface/modules/transformers_modules/internlm/internlm-xcomposer2-vl-7b/a52d70f582fa5773dd7b297f3e1a4caf149dcf59/modeling_internlm_xcomposer2.py", line 116, in encode_img
assert isinstance(image, torch.Tensor)
AssertionError
```
So if the finetuning following [guidance](https://github.com/InternLM/InternLM-XComposer/blob/main/finetune/README.md#internlm-xcomposer2-finetuning) is finished (each sample in JSON file consists of 1 or multiple images), how to evalute the performance on a new dataset in which each sample consists of 1 or multiple images as well? Thank you in advance!