[Model] Automatic conversion of TokenClassification model

[noooop]

Purpose

fix #30107

Test Plan

tests/models/registry.py
tests/models/language/pooling/test_token_classification.py

Test Result

pass

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• The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
• The test plan, such as providing test command.
• The test results, such as pasting the results comparison before and after, or e2e results
• (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.
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[gemini-code-assist]

Code Review

This pull request introduces automatic conversion for TokenClassification models. This is achieved by adding a mapping for the ForTokenClassification model architecture suffix to treat it as a pooling/classification task, and enhancing the ModelForSequenceClassification adapter to dynamically handle score.bias from model checkpoints. A new test case for a Qwen3-based token classification model is also added to verify the changes. The implementation appears correct and is a good enhancement for robust model conversion. I have not found any issues of high or critical severity.