from pytorch_lightning import Trainer
from flash.core.data import download_data
from flash.text import TextClassificationData, TextClassifier
if __name__ == "__main__":
# 1. Download the data
download_data("https://pl-flash-data.s3.amazonaws.com/imdb.zip", 'data/')
# 2. Load the model from a checkpoint
model = TextClassifier.load_from_checkpoint("https://flash-weights.s3.amazonaws.com/text_classification_model.pt")
# 2a. Classify a few sentences! How was the movie?
predictions = model.predict([
"Turgid dialogue, feeble characterization - Harvey Keitel a judge?.",
"The worst movie in the history of cinema.",
"I come from Bulgaria where it 's almost impossible to have a tornado."
"Very, very afraid"
"This guy has done a great job with this movie!",
])
print(predictions)
# 2b. Or generate predictions from a sheet file!
datamodule = TextClassificationData.from_file(
predict_file="data/imdb/predict.csv",
input="review",
)
predictions = Trainer().predict(model, datamodule=datamodule)
print(predictions)
from flash.text import TextClassificationData, TextClassifier
# 1. Download the data
download_data("https://pl-flash-data.s3.amazonaws.com/imdb.zip", "data/")
# 2. Load the model from a checkpoint
model = TextClassifier.load_from_checkpoint(
"https://flash-weights.s3.amazonaws.com/text_classification_model.pt")
model.serializer = Labels()
# 2a. Classify a few sentences! How was the movie?
predictions = model.predict([
"Turgid dialogue, feeble characterization - Harvey Keitel a judge?.",
"The worst movie in the history of cinema.",
"I come from Bulgaria where it 's almost impossible to have a tornado.",
"Very, very afraid.",
"This guy has done a great job with this movie!",
])
print(predictions)
# 2b. Or generate predictions from a sheet file!
datamodule = TextClassificationData.from_file(
predict_file="data/imdb/predict.csv",
input="review",
# use the same data pre-processing values we used to predict in 2a
preprocess=model.preprocess,
)
predictions = Trainer().predict(model, datamodule=datamodule)
print(predictions)
