Update README.md

README.md

@@ -317,12 +317,13 @@ cd skywork-r1v/inference
 ### 2. Set Up the Environment
 
 ```shell
-conda create -n r1-v python=3.10
-conda activate r1-v
-bash setup.sh
+conda create -n r1v-vllm python=3.12
+conda activate r1v-vllm
+pip install -U vllm
 ```
 
 ### 3. Run the Inference Script
+# transformers inference
 
 ```shell
 CUDA_VISIBLE_DEVICES="0,1" python inference_with_transformers.py \
@@ -330,12 +331,30 @@ CUDA_VISIBLE_DEVICES="0,1" python inference_with_transformers.py \
     --image_paths image1_path \
     --question "your question"
 ```
+# vllm inference
+```shell
+python inference_with_vllm.py \
+    --model_path path \
+    --image_paths image1_path image2_path \
+    --question "your question" \
+    --tensor_parallel_size 4
+```
 
 ---
 
 ## 4. Citation
 If you use Skywork-R1V in your research, please cite:
 
+```
+@misc{chris2025skyworkr1v2,
+    title        = {Skywork R1V2: Visual Hybrid Reinforcement Learning for Multimodal Reasoning},
+    author       = {Chris and Yichen Wei and Peng Yi and Xiaokun Wang and Weijie Qiu and Wei Shen and Tianyidan Xie and Jiangbo Pei and Jianhao Zhang and Yunzhuo Hao and Xuchen Song and Yang Liu and Yahui Zhou},
+    year         = {2025},
+    institution  = {Skywork AI, Kunlun Inc.},
+    howpublished = {\url{https://github.com/SkyworkAI/Skywork-R1V/blob/main/Skywork_R1V2.pdf}},
+}
+```
+
 ```
 @misc{peng2025skyworkr1vpioneeringmultimodal,
       title={Skywork R1V: Pioneering Multimodal Reasoning with Chain-of-Thought},