Hi everyone,
I have two models of the Trainer 1 class from Transformers lib.
In particular:
trainer1 = Trainer(
        model=model1,
        args=training_args,
        train_dataset=train_dataset,
        eval_dataset=eval_dataset,
        compute_metrics=compute_metrics,
    )

trainer2 = Trainer(
        model=model2,
        args=training_args,
        train_dataset=train_dataset,
        eval_dataset=eval_dataset,
        compute_metrics=compute_metrics,
    )

both models were trained (trainer.train(model_path=...) trainer.save_model()) on the same dataset to which I made some changes.
Now my problem is that I necessarily need to merge these two models (merge their weights (does that make sense?) or something like that) before doing the evaluation (trainer.evaluate()) and prediction (trainer.predict(test_dataset)) operations.
How can I do?
Do you have any suggestions?
P.s. The important thing is that the model resulting from the union/merge of these two models always has a Trainer type.
Thanks in advance!