oov_token=1, sos_token=2, eos_token=3, max_size=30) # max size of generated sentence in prediction mode model.fit(training_set, test_set, lr=0.001, batch_size=64, n_epochs=20, patience=2) model.save(path_to_save_models + 'my_model.pt') else: model = seq2seqModel.load(path_to_save_models + 'pretrained_moodle.pt') to_test = [ 'I am a student.', 'I have a red car.', # inversion captured 'I love playing video games.', 'This river is full of fish.', # plein vs pleine (accord) 'The fridge is full of food.', 'The cat fell asleep on the mat.', 'my brother likes pizza.', # pizza is translated to 'la pizza' 'I did not mean to hurt you', # translation of mean in context 'She is so mean', 'Help me pick out a tie to go with this suit!', # right translation "I can't help but smoking weed", # this one and below: hallucination 'The kids were playing hide and seek', 'The cat fell asleep in front of the fireplace'
oov_token=1, sos_token=2, eos_token=3, max_size=30) # max size of generated sentence in prediction mode model.fit(training_set, test_set, lr=0.001, batch_size=64, n_epochs=2, patience=2) model.save(path_to_save_models + 'my_model.pt') else: model = seq2seqModel.load(path_to_save_models + 'pretrained_moodle.pt', vocab_source_inv) to_test = [ 'I am a student', 'I have a red car.', # inversion captured 'I love playing video games.', 'This river is full of fish.', # plein vs pleine (accord) 'The fridge is full of food.', 'The cat fell asleep on the mat.', 'my brother likes pizza.', # pizza is translated to 'la pizza' 'I did not mean to hurt you', # translation of mean in context 'She is so mean', 'Help me pick out a tie to go with this suit!', # right translation "I can't help but smoking weed", # this one and below: hallucination 'The kids were playing hide and seek', 'The cat fell asleep in front of the fireplace'