[models] - fix: model loading - #89
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- Standardizes the model initialization process in multiple classes to ensure consistency and reduce redundancy. - Simplifies the model building logic by directly using the provided model instead of re-instantiating it.
- Implement tests to verify that custom transformer models load and utilize pretrained encoders correctly. - Ensure that the model configurations and outputs are validated for different model types.
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Summary
The custom model wrappers were loading a pretrained model, then replacing it with a new custom encoder.
This PR loads the custom encoder once and reuses it across BERT, DeeBERT, BERxiT, and Theseus. It also removes the DeeBERT and BERxiT weight initialization that was wiping loaded weights.
Added offline checkpoint tests for DeeBERT, BERxiT, and Theseus.
Testing
pytest -q tests/test_custom_model_initialization.py