Add install instructions for Windows GPU

README.md

@@ -131,6 +131,7 @@ The following table indicates the compatibility between versions of
 | `torchcodec`       | `torch`            | Python              |
 | ------------------ | ------------------ | ------------------- |
 | `main` / `nightly` | `main` / `nightly` | `>=3.10`, `<=3.13`   |
+| `0.7`              | `2.8`              | `>=3.9`, `<=3.13`   |
 | `0.6`              | `2.8`              | `>=3.9`, `<=3.13`   |
 | `0.5`              | `2.7`              | `>=3.9`, `<=3.13`   |
 | `0.4`              | `2.7`              | `>=3.9`, `<=3.13`   |
@@ -162,10 +163,6 @@ format you want. Refer to Nvidia's GPU support matrix for more details
    conda install "ffmpeg<8" -c conda-forge
    ```
 
-   If you are building FFmpeg from source you can follow Nvidia's guide to
-   configuring and installing FFmpeg with NVDEC support
-   [here](https://docs.nvidia.com/video-technologies/video-codec-sdk/12.0/ffmpeg-with-nvidia-gpu/index.html).
-
    After installing FFmpeg make sure it has NVDEC support when you list the supported
    decoders:
 
@@ -181,17 +178,25 @@ 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 -
    ```
 
-3. Install TorchCodec by passing in an `--index-url` parameter that corresponds
-   to your CUDA Toolkit version, example:
+3. Install TorchCodec
 
-   ```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
-   ```
+   - **On Linux**, 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
+     ```
+
+     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`:
 
-   Note that without passing in the `--index-url` parameter, `pip` installs
-   the CPU-only version of TorchCodec.
+     ```bash
+     conda install torchcodec -c conda-forge
+     ```
 
 ## Benchmark Results