Better instructions

Author: NicolasHug

README.md

@@ -146,12 +146,7 @@ First, make sure you have a GPU that has NVDEC hardware that can decode the
 format you want. Refer to Nvidia's GPU support matrix for more details
 [here](https://developer.nvidia.com/video-encode-and-decode-gpu-support-matrix-new).
 
-1. Install Pytorch corresponding to your CUDA Toolkit using the
-   [official instructions](https://pytorch.org/get-started/locally/). You'll
-   need the `libnpp` and `libnvrtc` CUDA libraries, which are usually part of
-   the CUDA Toolkit.
-
-2. Install or compile FFmpeg with NVDEC support.
+1. Install FFmpeg with NVDEC support.
    TorchCodec with CUDA should work with FFmpeg versions in [4, 7].
 
    If FFmpeg is not already installed, or you need a more recent version, an
@@ -178,25 +173,36 @@ format you want. Refer to Nvidia's GPU support matrix for more details
    ffmpeg -hwaccel cuda -hwaccel_output_format cuda -i test/resources/nasa_13013.mp4 -f null -
    ```
 
+#### Linux
+
+2. Install Pytorch corresponding to your CUDA Toolkit using the
+   [official instructions](https://pytorch.org/get-started/locally/). You'll
+   need the `libnpp` and `libnvrtc` CUDA libraries, which are usually part of
+   the CUDA Toolkit.
+
+
 3. Install TorchCodec
 
-   - **On Linux**, pass in an `--index-url` parameter that corresponds
-     to your CUDA Toolkit version, for example:
+   Pass in an `--index-url` parameter that corresponds to your CUDA Toolkit
+   version, for example:
 
-     ```bash
-     # This corresponds to CUDA Toolkit version 12.6. It should be the same one
-     # you used when you installed PyTorch (If you installed PyTorch with pip).
-     pip install torchcodec --index-url=https://download.pytorch.org/whl/cu126
-     ```
+   ```bash
+   # This corresponds to CUDA Toolkit version 12.6. It should be the same one
+   # you used when you installed PyTorch (If you installed PyTorch with pip).
+   pip install torchcodec --index-url=https://download.pytorch.org/whl/cu126
+   ```
 
-     Note that without passing in the `--index-url` parameter, `pip` installs
-     the CPU-only version of TorchCodec.
+   Note that without passing in the `--index-url` parameter, `pip` installs
+   the CPU-only version of TorchCodec.
 
-   - **On Windows** (experimental support), you'll need to rely on `conda`:
+#### Windows
 
-     ```bash
-     conda install torchcodec -c conda-forge
-     ```
+On Windows (experimental support), you'll need to rely on `conda` to install
+both pytorch and TorchCodec:
+
+```bash
+conda install -c conda-forge torchcodec=*=*cuda*
+```
 
 ## Benchmark Results