camel_tools.sentiment¶
This module contains the CAMeL Tools sentiment analyzer component.
Classes¶
-
class
camel_tools.sentiment.
SentimentAnalyzer
(model_path)¶ A class for running a fine-tuned sentiment analysis model to predict the sentiment of given sentences.
-
static
labels
()¶ Get the list of possible sentiment labels returned by predictions.
Returns: List of sentiment labels. Return type: list
ofstr
-
predict
(sentences)¶ Predict the sentiment labels of a list of sentences.
Parameters: sentences ( list
ofstr
) – Input sentences.Returns: The predicted sentiment labels for given sentences. Return type: list
ofstr
-
predict_sentence
(sentence)¶ Predict the sentiment label of a single sentence.
Parameters: sentence ( str
) – Input sentence.Returns: The predicted sentiment label for given sentence. Return type: str
-
static
pretrained
(model_name=None)¶ Load a pre-trained model provided with camel_tools.
Parameters: model_name ( str
, optional) – Name of pre-trained model to load. Two models are available: ‘arabert’ and ‘mbert’. If None, the default model (‘arabert’) will be loaded. Defaults to None.Returns: Instance with loaded pre-trained model. Return type: SentimentAnalyzer
-
static
Examples¶
Below is an example of how to load and use the default pre-trained model.
from camel_tools.sentiment import SentimentAnalyzer
sa = SentimentAnalyzer.pretrained()
# Predict the sentiment of a single sentence
sentiment = sa.predict_sentence('أنا بخير')
# Predict the sentiment of multiple sentences
sentences = [
'أنا بخير',
'أنا لست بخير'
]
sentiments = sa.predict(sentences)