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[CVPR 2024 Oral] InternVL Family: A Pioneering Open-Source Alternative to GPT-4o. 接近GPT-4o表现的开源多模态对话模型

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### Motivation 我是使用 hugging face 方式推論 OpenGVLab/InternVL2-8B 模型,請問模型輸出是否有提供 confidence score 的參數? 謝謝! ### Related resources _No response_ ### Additional context _No response_

### 📚 The doc issue 请问InternVL2的grounding和多图任务使用了哪些数据集?预训练和微调阶段都涵盖了这两类任务吗? ### Suggest a potential alternative/fix _No response_

### Motivation 如题,grad_norm很快降为0.5左右,是什么参数不对吗? 资源:1*A100 80G 训练参数: deepspeed --include localhost:2 \ llava/train/train_mem.py \ --deepspeed ./scripts/zero2.json \ --model_name_or_path $DATA_HOME/pretrained_mm_projector/vicuna-7b-v1.5 \ --version plain \ --data_path $DATA_HOME/LLaVA-Pretrain/enhanced_llava_pretrain_data_708K.json \ --image_folder $DATA_HOME/LLaVA-Pretrain/images \ --vision_tower $DATA_HOME/pretrained_mm_projector/InternViT-300M-448px \...

### 📚 The doc issue I'm confused about the internvl_c_retrieval and internvl_g_retrieval ,what's the different? and the video_retrieval can an example replace it? ### Suggest a potential alternative/fix could you...

### 📚 The doc issue 请问如果想让模型输出固定长度(大概在这个范围即可),比如输出长度为200个token,该怎么给prompt比较好 ### Suggest a potential alternative/fix 需要解答

### Motivation 您好, 我想返回 InternVL2‑26B的output_attentions,但是使用transformer推理时,发现,在模型自带的代码里面,不论外面设置output_attentions为True或者False,modeling_internlm2.py代码里面都将其人工设定为False,导致无法返回attn_weights,如果要返回有效的attn_weights,应该怎么修改代码? 感谢。 ### Related resources _No response_ ### Additional context _No response_

I have made some experiments on the chat demo, and found InternVL2-Pro is amazing! Could you tell how large InternVL2-Pro is and when to release its model? And will there...

### Checklist - [ ] 1. I have searched related issues but cannot get the expected help. - [ ] 2. The bug has not been fixed in the latest...

### Checklist - [X] 1. I have searched related issues but cannot get the expected help. - [X] 2. The bug has not been fixed in the latest version. -...

直接用device_map="auto" 或 device_map="balanced_low_0" 会报错,text_embeds = text_embeds[torch.arange(text_embeds.shape[0]), attention_mask.sum(1) - 1] RuntimeError: indices should be either on cpu or on the same device as the indexed tensor (cuda:1)