Fix Apertus model loading (NotImplementedError: Cannot copy out of meta tensor; no data!)
Author: xenova
Pull request: yes


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Fixes issue related to loading Apertus models to meta device. Reproduction:
```py
>>> from transformers import AutoModelForCausalLM
>>> AutoModelForCausalLM.from_pretrained('onnx-internal-testing/tiny-random-ApertusForCausalLM')
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
    AutoModelForCausalLM.from_pretrained('onnx-internal-testing/tiny-random-ApertusForCausalLM')
    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File ".../transformers/src/transformers/models/auto/auto_factory.py", line 372, in from_pretrained
    return model_class.from_pretrained(
           ~~~~~~~~~~~~~~~~~~~~~~~~~~~^
        pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    )
    ^
  File ".../transformers/src/transformers/modeling_utils.py", line 4072, in from_pretrained
    model = cls(config, *model_args, **model_kwargs)
  File ".../transformers/src/transformers/models/apertus/modeling_apertus.py", line 440, in __init__
    self.model = ApertusModel(config)
                 ~~~~~~~~~~~~^^^^^^^^
  File ".../transformers/src/transformers/models/apertus/modeling_apertus.py", line 361, in __init__
    [ApertusDecoderLayer(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]
     ~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^
  File ".../transformers/src/transformers/models/apertus/modeling_apertus.py", line 296, in __init__
    self.mlp = ApertusMLP(config)
               ~~~~~~~~~~^^^^^^^^
  File ".../transformers/src/transformers/models/apertus/modeling_apertus.py", line 50, in __init__
    self.act_fn = ACT2FN[config.hidden_act]
                  ~~~~~~^^^^^^^^^^^^^^^^^^^
  File ".../transformers/src/transformers/activations.py", line 221, in __getitem__
    return cls(**kwargs)
  File ".../transformers/src/transformers/activations.py", line 250, in __init__
    self._beta_scalar = float(self.beta.detach().cpu().float().item())
                              ~~~~~~~~~~~~~~~~~~~~~~^^
  File "/Library/Frameworks/Python.framework/Versions/3.13/lib/python3.13/site-packages/torch/utils/_device.py", line 103, in __torch_function__
    return func(*args, **kwargs)
NotImplementedError: Cannot copy out of meta tensor; no data!
```


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@Cyrilvallez 

Comments:
An alternative approach is to register `self._beta_scalar` and `self._eps_scalar` as properties that simply type-cast (`float(...)`) the buffers at runtime.

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