Update README.md

README.md

@@ -68,7 +68,13 @@ pip install -e ".[train]"
 ### B. Inference
 
 ```bash
-CUDA_VISIBLE_DEVICES=0 python infer.py --model_dir /path/to/your/model
+git clone https://github.com/deepglint/unicom
+cd unicom
+pip install --upgrade pip
+pip install -e ".[train]"
+pip install flash-attn --no-build-isolation
+
+CUDA_VISIBLE_DEVICES=0 python infer.py --model_dir DeepGlint-AI/MLCD-Embodied-7B
 
 # example:
 # >> Enter 'exit' to end the conversation, 'reset' to clear the chat history.
@@ -77,6 +83,9 @@ CUDA_VISIBLE_DEVICES=0 python infer.py --model_dir /path/to/your/model
 # >> Assistant: The image features a stylized representation of a cat, characterized by its vibrant and abstract depiction.
 # >> User: What color is this cat?
 # >> Assistant: The cat in the image is primarily white with blue, orange and pink accents, creating a visually appealing and unique appearance.
+# >> User: <image>请你介绍一下这个图片
+# >> Assistant: 这是一幅充满创意的猫头艺术作品。它采用了多色渐变和抽象风格，将猫的头部描绘成一个充满活力和色彩的视觉冲击。猫的眼睛用金色渲染，显得非常有神采，
+# 而粉色的鼻子则增添了一丝可爱感。整体设计融合了现代艺术与传统猫头图案，创造出一种既独特又引人入胜的视觉效果。。
 ```
 
 ### C. Evaluation for Embodied Ability
@@ -132,7 +141,17 @@ bash scripts/eval/eval_robo.sh /path/to/your/model
 Install the evaluation tool and execute the evaluation script:
 ```bash
 pip install lmms-eval==0.2.0
-bash eval.sh
+PYTHONPATH=./ CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 python -m accelerate.commands.launch \
+    --main_process_port=12444 \
+    --num_processes=8 \
+    -m lmms_eval \
+    --model llava \
+    --model_args pretrained=DeepGlint-AI/MLCD-Embodied-7B,conv_template=qwen_1_5 \
+    --tasks mme \
+    --batch_size 1 \
+    --log_samples \
+    --log_samples_suffix mlcd \
+    --output_path ./eval_log/
 ```
 
 We would like to express our gratitude to [Huajie Tan](https://huggingface.co/tanhuajie2001), [Yumeng Wang](https://huggingface.co/devymex), [Yin Xie](https://huggingface.co/Yin-Xie) for his significant contributions to the experimental validation in MLLMs.