Add FA2 fallback (kernel) support to the modernbert model
Author: YangKai0616
Pull request: yes

# What does this PR do?

1. Add **FA2** fallback (kernel) support to the `modernbert` model.
Related UT: 
```
FAILED tests/models/pe_audio/test_modeling_pe_audio.py::PeAudioModelTest::test_cpu_offload - KeyError: 'kernels-community/flash-attn2'
FAILED tests/models/pe_audio/test_modeling_pe_audio.py::PeAudioModelTest::test_determinism - KeyError: 'kernels-community/flash-attn2'
FAILED tests/models/pe_audio/test_modeling_pe_audio.py::PeAudioModelTest::test_disk_offload_bin - KeyError: 'kernels-community/flash-attn2'
FAILED tests/models/pe_audio/test_modeling_pe_audio.py::PeAudioModelTest::test_disk_offload_safetensors - KeyError: 'kernels-community/flash-attn2'
FAILED tests/models/pe_audio/test_modeling_pe_audio.py::PeAudioModelTest::test_model - KeyError: 'kernels-community/flash-attn2'
FAILED tests/models/pe_audio/test_modeling_pe_audio.py::PeAudioModelTest::test_model_outputs_equivalence - KeyError: 'kernels-community/flash-attn2'
FAILED tests/models/pe_audio/test_modeling_pe_audio.py::PeAudioModelTest::test_model_parallelism - KeyError: 'kernels-community/flash-attn2'
```

2. When FA2 is available, `tests/models/pe_audio/test_modeling_pe_audio.py::PeAudioModelTest::test_init_weights_can_init_buffers` will report an error 
```AssertionError: False is not true : The following buffers are not properly handled in `_init_weights()` (the model should be able to reinitialize them correctly if t...```.

Root cause: The `inv_freq` buffer in `ModernBertUnpaddedRotaryEmbedding` (inherited from `flash_attn's 
RotaryEmbedding`) was not properly initialized when loading from meta device. Added 
reinitialization logic in `_init_weights()` to compute and copy correct `inv_freq` values.

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Models:

- text models: @ArthurZucker @Cyrilvallez
- vision models: @yonigozlan @molbap
- audio models: @eustlb @ebezzam @vasqu
- multimodal models: @zucchini-nlp
- graph models: @clefourrier

Library:

- generate: @zucchini-nlp (visual-language models) or @gante (all others)
- continuous batching: @remi-or @ArthurZucker @McPatate
- pipelines: @Rocketknight1
- tokenizers: @ArthurZucker and @itazap
- trainer: @SunMarc
- attention: @vasqu @ArthurZucker @CyrilVallez
- model loading (from pretrained, etc): @CyrilVallez
- distributed: @3outeille @ArthurZucker
- CIs: @ydshieh

Integrations:

- ray/raytune: @richardliaw, @amogkam
- Big Model Inference: @SunMarc
- quantization: @SunMarc @MekkCyber
- kernels: @MekkCyber @drbh
- peft: @BenjaminBossan @githubnemo

Devices/Backends:

- AMD ROCm: @ivarflakstad
- Intel XPU: @IlyasMoutawwakil
- Ascend NPU: @ivarflakstad 

Documentation: @stevhliu

Research projects are not maintained and should be taken as is.

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Comments:
Hey, @vasqu , pls help review. Thx!

**[For maintainers]** Suggested jobs to run (before merge)

run-slow: modernbert