Bug fix 5875873 (#865)

## What does this PR do?

**Type of change:** Bug fix <!-- Use one of the following: Bug fix, new
feature, new example, new tests, documentation. -->

**Overview:** Newer version of trl uses dtype instead of torch_dtype.
Modified code to set float32 as default for older versions of trl that
you torch_dtype.

## Usage
<!-- You can potentially add a usage example below. -->

```python
# Add a code snippet demonstrating how to use this
```

## Testing
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- **Make sure you read and follow [Contributor
guidelines](https://github.com/NVIDIA/Model-Optimizer/blob/main/CONTRIBUTING.md)**
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- **Is this change backward compatible?**: Yes/No <!--- If No, explain
why. -->
- **Did you write any new necessary tests?**: Yes/No
- **Did you add or update any necessary documentation?**: Yes/No
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[Changelog](https://github.com/NVIDIA/Model-Optimizer/blob/main/CHANGELOG.rst)?**:
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## Additional Information
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<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->

## Summary by CodeRabbit

* **Bug Fixes**
* Enhanced error handling in model training examples to safely manage
missing dtype attributes, preventing crashes during initialization when
torch_dtype is not configured.

<!-- end of auto-generated comment: release notes by coderabbit.ai -->

---------

Signed-off-by: Suguna Velury <178320438+sugunav14@users.noreply.github.com>

Author: sugunav14

examples/gpt-oss/sft.py

@@ -72,7 +72,7 @@ def main(script_args, training_args, model_args, quant_args):
         "revision": model_args.model_revision,
         "trust_remote_code": model_args.trust_remote_code,
         "attn_implementation": model_args.attn_implementation,
-        "torch_dtype": model_args.torch_dtype,
+        "torch_dtype": getattr(model_args, "dtype", "float32"),
         "use_cache": not training_args.gradient_checkpointing,
     }