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README.md

@@ -12,7 +12,7 @@ Language: **English** | [**中文**](https://huggingface.co/Tencent-Hunyuan/Tens
 
 We provide a TensorRT version of [HunyuanDiT](https://github.com/Tencent/HunyuanDiT) for inference acceleration 
 (faster than flash attention). One can convert the torch model to TensorRT model using the following steps based on
-**TensorRT-9.2.0.5** and **cuda (11.7 or 11.8)**.
+**TensorRT-10.1.0.27** and **cuda (11.7 or 11.8)**.
 
 > ⚠️ Important Reminder (Suggestion for testing the TensorRT acceleration version):  
 > We recommend users to test the TensorRT version on NVIDIA GPUs with Compute Capability >= 8.0,(For example, RTX4090, 
@@ -68,12 +68,22 @@ ln -s ${REMOTE_PATH} ./ckpts/t2i/model_trt/engine/model_onnx.plan
 
 If you are using a different GPU, you can build the engine using the following command.
 
+##### Hunyuan-DiT v1.2
+
 ```shell
 # Build the TensorRT engine. By default, it will read the `ckpts` folder in the current directory.
 sh trt/build_engine.sh
 ```
 
-Finally, if you see the output like `&&&& PASSED TensorRT.trtexec [TensorRT v9200]`, the engine is built successfully.
+##### Using Previous versions,  Hunyuan-DiT <= v1.1
+```shell
+# v1.1 
+sh trt/build_engine.sh 1.1
+# v1.0 
+sh trt/build_engine.sh 1.0
+```
+
+Finally, if you see the output like `&&&& PASSED TensorRT.trtexec [TensorRT v10100]`, the engine is built successfully.
 
 ### 4. Run the inference using the TensorRT model.