Update README.md

README.md

@@ -81,18 +81,14 @@ Once the environment is activated, install the necessary packages.
 
 Although inference can run efficiently on a CPU, you may need a GPU for training more resource-intensive downstream tasks. Visit [this page](https://pytorch.org/get-started/locally/) and select the appropriate options based on your system's specifications. The website will generate a tailored installation command.
 
-For instance, on an NVIDIA system, use a command like the following with the appropriate CUDA version for your system:
+For instance, on an NVIDIA system, you can use a command like the following with the appropriate CUDA version for your system:
 
 ```bash
-conda install pytorch pytorch-cuda=12.1 -c pytorch -c nvidia
+conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia
 ```
 
 This command installs PyTorch with CUDA support for GPU-accelerated training. Ensure that the specified CUDA version is compatible with your system, adjusting it if necessary.
 
-```bash
-conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia
-```
-
 > **Note:** If you encounter issues installing CUDA-enabled PyTorch, verify your CUDA version compatibility. It might also be due to conflicting installation attempts—try a fresh environment.
 
 #### **Install Other Required Packages via Conda Forge**