[Bug] How do I use this?

- [x ] I didn't find a similar issue already open.
- [x ] I read the documentation (README AND Wiki)
- [x ] I have installed FFMpeg
- [x ] My problem is related to Spleeter only, not a derivative product (such as Webapplication, or GUI provided by others)

## Description

The google colab provided in the readme doesn't work.

I've tried running it locally with Python 3.12 - said I needed 3.10. Then I downgraded to 3.10, but it's still not working as I get this error
```
A module that was compiled using NumPy 1.x cannot be run in
NumPy 2.2.6 as it may crash. To support both 1.x and 2.x
versions of NumPy, modules must be compiled with NumPy 2.0.
Some module may need to rebuild instead e.g. with 'pybind11>=2.12'.

If you are a user of the module, the easiest solution will be to
downgrade to 'numpy<2' or try to upgrade the affected module.
We expect that some modules will need time to support NumPy 2.
```
So from what I understand, I need some sort of legacy setup with old versions of everything to run this?

## Step to reproduce

1. Installed using `pip install spleeter`
2. Run as `spleeter separate -p spleeter:2stems -o output audio_example.mp3`
3. Got
```
A module that was compiled using NumPy 1.x cannot be run in
NumPy 2.2.6 as it may crash. To support both 1.x and 2.x
versions of NumPy, modules must be compiled with NumPy 2.0.
Some module may need to rebuild instead e.g. with 'pybind11>=2.12'
```
error

## Output

```bash
A module that was compiled using NumPy 1.x cannot be run in
NumPy 2.2.6 as it may crash. To support both 1.x and 2.x
versions of NumPy, modules must be compiled with NumPy 2.0.
Some module may need to rebuild instead e.g. with 'pybind11>=2.12'.

If you are a user of the module, the easiest solution will be to
downgrade to 'numpy<2' or try to upgrade the affected module.
We expect that some modules will need time to support NumPy 2.
```

## Environment

| | |
| ----------------- | ------------------------------- |
| OS | Windows |
| Installation type | pip |
| RAM available | 16GB |
| Hardware spec | - |