How to do you load a model from a checkpoint using simple transformers?
Question:
I am using the simple transformers library, I have just finished training a model and now I want to load it to try making some predictions. However, I must be doing something wrong because it keeps raising an error. Here is my code:
from simpletransformers.seq2seq import Seq2SeqModel
model = Seq2SeqModel("marian","outputs/best_model")
print(model)
print(model.predict(["Using AI to Accelerate Scientific Discovery"]))
Here is the error it displays:
ValueError: You must specify a Seq2Seq config OR encoder_type, encoder_name, and decoder_name OR encoder_type and encoder_decoder_name
I have tried to search up answers from the documentation but I couldn’t find anything.
Answers:
The error message "You must specify a Seq2Seq config OR encoder_type, encoder_name, and decoder_name OR encoder_type and encoder_decoder_name" indicates that the Seq2SeqModel class is unable to find the necessary configuration information to initialize the model.
The Seq2SeqModel class requires a configuration file to specify the model architecture and training parameters. This configuration file should be saved in the model directory that you provide as the second argument to the Seq2SeqModel constructor.
To fix the error, you need to ensure that the model directory contains a configuration file. You can specify the path to the configuration file when you instantiate the Seq2SeqModel class using the config argument.
For example:
from simpletransformers.seq2seq import Seq2SeqModel
model = Seq2SeqModel("marian", "outputs/best_model",
config="outputs/best_model/config.json")
If you are not sure where the configuration file is saved, you can check the documentation for the simpletransformers library or the training script that you used to train the model.
Once you have provided the correct path to the configuration file, you should be able to instantiate the Seq2SeqModel class and use the predict method to generate predictions.
I hope this helps
I am using the simple transformers library, I have just finished training a model and now I want to load it to try making some predictions. However, I must be doing something wrong because it keeps raising an error. Here is my code:
from simpletransformers.seq2seq import Seq2SeqModel
model = Seq2SeqModel("marian","outputs/best_model")
print(model)
print(model.predict(["Using AI to Accelerate Scientific Discovery"]))
Here is the error it displays:
ValueError: You must specify a Seq2Seq config OR encoder_type, encoder_name, and decoder_name OR encoder_type and encoder_decoder_name
I have tried to search up answers from the documentation but I couldn’t find anything.
The error message "You must specify a Seq2Seq config OR encoder_type, encoder_name, and decoder_name OR encoder_type and encoder_decoder_name" indicates that the Seq2SeqModel class is unable to find the necessary configuration information to initialize the model.
The Seq2SeqModel class requires a configuration file to specify the model architecture and training parameters. This configuration file should be saved in the model directory that you provide as the second argument to the Seq2SeqModel constructor.
To fix the error, you need to ensure that the model directory contains a configuration file. You can specify the path to the configuration file when you instantiate the Seq2SeqModel class using the config argument.
For example:
from simpletransformers.seq2seq import Seq2SeqModel
model = Seq2SeqModel("marian", "outputs/best_model",
config="outputs/best_model/config.json")
If you are not sure where the configuration file is saved, you can check the documentation for the simpletransformers library or the training script that you used to train the model.
Once you have provided the correct path to the configuration file, you should be able to instantiate the Seq2SeqModel class and use the predict method to generate predictions.
I hope this helps