Module rust_bert::pipelines::sentiment

Sentiment Analysis pipeline

Predicts the binary sentiment for a sentence. By default, the dependencies for this model will be downloaded for a DistilBERT model finetuned on SST-2. Customized DistilBERT models can be loaded by overwriting the resources in the configuration. The dependencies will be downloaded to the user's home directory, under ~/.cache/.rustbert/distilbert-sst2

use rust_bert::pipelines::sentiment::SentimentModel;

let sentiment_classifier = SentimentModel::new(Default::default())?;
let input = [
    "Probably my all-time favorite movie, a story of selflessness, sacrifice and dedication to a noble cause, but it's not preachy or boring.",
    "This film tried to be too many things all at once: stinging political satire, Hollywood blockbuster, sappy romantic comedy, family values promo...",
    "If you like original gut wrenching laughter you will like this movie. If you are young or old then you will love this movie, hell even my mom liked it.",
];
let output = sentiment_classifier.predict(&input);

(Example courtesy of IMDb)

Output:

[
   Sentiment { polarity: Positive, score: 0.998 },
   Sentiment { polarity: Negative, score: 0.992 },
   Sentiment { polarity: Positive, score: 0.999 }
]

Structs

Sentiment	Sentiment returned by the model.
SentimentConfig	Configuration for sentiment classification
SentimentModel	SentimentClassifier to perform sentiment analysis

Enums

SentimentPolarity

Enum with the possible sentiment polarities. Note that the pre-trained SST2 model does not include neutral sentiment.

Functions

ss2_processor