Adapt cebra.save and cebra.load functions for upcoming torch.load changes

[stes]

Due to an upcoming change in pytorch, we need to make the cebra.save function future proof:

cebra/integrations/sklearn/cebra.py:1453: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
    checkpoint = torch.load(filename, **kwargs)

Steps to implement:

• Specify torch.serialization.add_safe_globals in cebra.save
• Add a test checking for the current warning (should fail with current codebase) -> update and fix text

[stes]

Fixed with #221