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Call resume_training for base model in train CLI
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@ -234,7 +234,7 @@ def train(
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if base_model:
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if base_model:
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# Start with an existing model, use default optimizer
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# Start with an existing model, use default optimizer
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optimizer = create_default_optimizer(Model.ops)
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optimizer = nlp.resume_training(device=use_gpu)
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else:
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else:
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# Start with a blank model, call begin_training
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# Start with a blank model, call begin_training
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optimizer = nlp.begin_training(lambda: corpus.train_tuples, device=use_gpu)
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optimizer = nlp.begin_training(lambda: corpus.train_tuples, device=use_gpu)
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