LLaVA-NeXT demo code froze while running

[FrankFcc]

Trying to deploy and run demo on a 4 A6000 cluster but it seemed that the runtime froze without any exceptions... Could there be any possible problems? Sorry for asking a naive question and thanks for help...

Here is the cmd output: `bash scripts/video/demo/video_demo.sh lmms-lab/LLaVA-NeXT-Video-7B-DPO vicuna_v1 32 2 average after no_token True playground/demo/xU25MMA2N4aVtYay.mp4 Overwriting config with {'mm_spatial_pool_mode': 'average', 'mm_spatial_pool_stride': 2, 'mm_pooling_position': 'after', 'mm_newline_position': 'no_token', 'max_sequence_length': 8192, 'tokenizer_model_max_length': 8192} Delay load: True Loading checkpoint shards: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:02<00:00, 1.23it/s] Some weights of the model checkpoint at lmms-lab/LLaVA-NeXT-Video-7B-DPO were not used when initializing LlavaLlamaForCausalLM: ['model.vision_resampler.mm_projector.0.bias', 'model.vision_resampler.mm_projector.0.weight', 'model.vision_resampler.mm_projector.2.bias', 'model.vision_resampler.mm_projector.2.weight', 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• This IS expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
• This IS NOT expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).`