Upgrade dependencies

[dxqb]

There are some major upgrades of dependencies:

• transformers from 4.x to 5.0
• huggingface_hub from 0.34.x to 1.3.x
• Torch 2.10
• python 3.13
• CUDA 13.0

This PR upgrades all dependencies to their latest version (except ROCM).
huggingface_hub was held back by transformers so far. With transformers 5.0, huggingface_hub gets a major upgrade.

This is why I've enabled XET in this PR. Previous problems with XET might not apply anymore - to be tested.
If XET works well, #770 could be reverted because you don't need to download multiple files anymore to get full speed.
Would close #949

This PR superceedes #1189 and #1266 if we decide to merge it.

[dxqb]

updating to CUDA 13 might be too early:

/OneTrainer/venv/lib/python3.12/site-packages/torch/cuda/__init__.py:184: UserWarning: CUDA initialization: The NVIDIA driver on your system is too old (found version 12090). Please update your GPU driver by downloading and installing a new version from the URL: http://www.nvidia.com/Download/index.aspx Alternatively, go to: https://pytorch.org to install a PyTorch version that has been compiled with your version of the CUDA driver. (Triggered internally at /pytorch/c10/cuda/CUDAFunctions.cpp:119.)

[dxqb]

CUDA 12.8 instead. Even many RTX 5090 clouds are still on drivers not supported by CUDA 13

[dxqb]

can we allow python 3.13 after this?

[O-J1]

We can include it as part of the testing yes

[O-J1]

Self note: Tested and the scalene upgrade breaks on windows. Need to look into it

[dxqb]

Self note: Tested and the scalene upgrade breaks on windows. Need to look into it

or downgrade to that version, but leave a comment that scalene must not be upgraded. which version?