Error with pretrain T5 model for paraphrase

[LeMoussel]

On Colab environment, I pretrain T5 model on custom corpus.
When I make predictions with the pretrain T5 model, I got this error:

---------------------------------------------------------------------------

TypeError                                 Traceback (most recent call last)

[<ipython-input-11-4e80e7f36013>](https://localhost:8080/#) in <cell line: 20>()
     18 # https://simpletransformers.ai/docs/t5-model/#making-predictions-with-a-t5model
     19 prefix = "paraphrase"
---> 20 pred = t5_trained_model.predict([f"{prefix}: Je mange du fromage."])
     21 pprint(pred)
     22 

2 frames

[/usr/local/lib/python3.9/dist-packages/transformers/generation/utils.py](https://localhost:8080/#) in generate(self, inputs, generation_config, logits_processor, stopping_criteria, prefix_allowed_tokens_fn, synced_gpus, streamer, **kwargs)
   1370         )
   1371         is_beam_gen_mode = (
-> 1372             (generation_config.num_beams > 1)
   1373             and (generation_config.num_beam_groups == 1)
   1374             and generation_config.do_sample is False

TypeError: '>' not supported between instances of 'NoneType' and 'int'

Source code:

from pprint import pprint

args = {
    "overwrite_output_dir": True,
    "max_seq_length": 256,
    "max_length": 50,
    "top_k": 50,
    "top_p": 0.95,
    "num_return_sequences": 5,
}

# Initializing the T5 model 
# https://simpletransformers.ai/docs/t5-model/
t5_trained_model = T5Model("t5","/content/drive/MyDrive/Colab Notebooks/Data_Paraphrase/T5_fr_paraphrase")

# Generating paraphrases using the trained model
# https://simpletransformers.ai/docs/t5-model/#making-predictions-with-a-t5model
prefix = "paraphrase"
pred = t5_trained_model.predict([f"{prefix}: Je mange du fromage."])
pprint(pred)

Screenshot:

[LeMoussel]

Find the solution. I set args like this :

args = {
    "overwrite_output_dir": True,
    "max_seq_length": 256,
    "max_length": 50,
    "top_k": 50,
    "top_p": 0.95,
    "num_return_sequences": 3,
    "num_beams": 1,
}

and do:

# Initializing the T5 model 
# https://simpletransformers.ai/docs/t5-model/
t5_trained_model = T5Model("t5","/content/drive/MyDrive/Colab Notebooks/Data_Paraphrase/T5_fr_paraphrase", args=args)``

[Ch-rode]

hi @LeMoussel ! Thanks a lot for sharing the solution. I was desperate to make it work and fortunately I saw your post. Unfortunately If I am using your same set of parameters I have the following error: ValueError: Greedy methods without beam search do not support "num_return_sequences" different than 1 (got 3).