Fix Gemma2 dtype issue when storing weights in float16 precision
Author: Nerogar
Pull request: yes

# What does this PR do?

This change fixes an exception that can happen when storing Gemma2 weights in float16 format, but using a bfloat16 autocast context. In that case, `hidden_states` can be in bfloat16 format, while `attention_mask` is in float16 format. That will lead to the following error
```
    attention_mask = torch.where(sliding_window_mask, min_dtype, attention_mask)
RuntimeError: value cannot be converted to type at::Half without overflow
```

Using the min value of the `attention_mask` instead should be safe, since the value is only used in the torch.where operation.

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Comments:
Seems reasonable to me, cc @ArthurZucker 

Sure. I've done the rebase.

Should be fixed now @ArthurZucker. I also had to rebase onto main again because some tests were still failing.