Update transformers to support `FqnToConfig`
Author: jcaip
Pull request: yes

Summary:

This PR adds in support for `FqnToConfig` to transformers, which was added to torchao earlier in [this](https://github.com/pytorch/ao/pull/3083) PR. 

`FqnToConfig` adds support for quantizing parameters that are not called "weight". Previously torchao was linear only, so assuming "weight" was fine, but this is insufficient for quantizing moe models like llama4, as they register their parameters under different names (`gate_up_proj / down_proj`). 

Test Plan:
```
pytest tests/quantization/torchao_integration/test_torchao.py -k fqn_to_config
```

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Comments:
cc @mekkcyber for quantization

cc @SunMarc as well 

cc @MekkCyber @SunMarc friendly ping on review :) 

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

run-slow: torchao_integration

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