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README.md

@@ -34,7 +34,11 @@ huggingface-cli download Tencent-Hunyuan/TensorRT-libs --local-dir ./ckpts/t2i/m
 ### 2. Install the TensorRT dependencies.
 
 ```shell
+# Extract and install the TensorRT dependencies.
 sh trt/install.sh
+
+# Set the TensorRT build environment variables. We provide a script to set up the environment.
+source trt/activate.sh
 ```
 
 ### 3. Build the TensorRT engine.
@@ -42,18 +46,22 @@ sh trt/install.sh
 
 #### Method 1: Use the prebuilt engine
 
-We provide some prebuilt TensorRT engines. 
+We provide some prebuilt TensorRT engines, which need to be downloaded from Huggingface.
 
-|  Supported GPU   |                                                  Download Link                                                  |            Remote Path            |
-|:----------------:|:---------------------------------------------------------------------------------------------------------------:|:---------------------------------:|
-| GeForce RTX 3090 | [HuggingFace](https://huggingface.co/Tencent-Hunyuan/TensorRT-engine/blob/main/engines/RTX3090/model_onnx.plan) | `engines/RTX3090/model_onnx.plan` |
-| GeForce RTX 4090 | [HuggingFace](https://huggingface.co/Tencent-Hunyuan/TensorRT-engine/blob/main/engines/RTX4090/model_onnx.plan) | `engines/RTX4090/model_onnx.plan` |
-|       A100       |  [HuggingFace](https://huggingface.co/Tencent-Hunyuan/TensorRT-engine/blob/main/engines/A100/model_onnx.plan)   |  `engines/A100/model_onnx.plan`   |
+|  Supported GPU   |            Remote Path            |
+|:----------------:|:---------------------------------:|
+| GeForce RTX 3090 | `engines/RTX3090/model_onnx.plan` |
+| GeForce RTX 4090 | `engines/RTX4090/model_onnx.plan` |
+|       A100       |  `engines/A100/model_onnx.plan`   |
 
-Use the following command to download and place the engine in the specified location.
+Use the following command to download and place the engine in the specified location. 
+
+*Note: Please replace `<Remote Path>` with the corresponding remote path in the table above.*
 
 ```shell
-huggingface-cli download Tencent-Hunyuan/TensorRT-engine <Remote Path> --local-dir ./ckpts/t2i/model_trt/engine
+export REMOTE_PATH=<Remote Path>
+huggingface-cli download Tencent-Hunyuan/TensorRT-engine ${REMOTE_PATH} ./ckpts/t2i/model_trt/engine/
+ln -s ${REMOTE_PATH} ./ckpts/t2i/model_trt/engine/model_onnx.plan
 ```
 
 #### Method 2: Build your own engine
@@ -61,9 +69,6 @@ huggingface-cli download Tencent-Hunyuan/TensorRT-engine <Remote Path> --local-d
 If you are using a different GPU, you can build the engine using the following command.
 
 ```shell
-# Set the TensorRT build environment variables first. We provide a script to set up the environment.
-source trt/activate.sh
-
 # Build the TensorRT engine. By default, it will read the `ckpts` folder in the current directory.
 sh trt/build_engine.sh
 ```
@@ -73,6 +78,9 @@ Finally, if you see the output like `&&&& PASSED TensorRT.trtexec [TensorRT v920
 ### 4. Run the inference using the TensorRT model.
 
 ```shell
+# Important: If you have not activated the environment, please run the following command.
+source trt/activate.sh
+
 # Run the inference using the prompt-enhanced model + HunyuanDiT TensorRT model.
 python sample_t2i.py --prompt "渔舟唱晚" --infer-mode trt