This model is used for sentiment analysis on english yelp reviews.
It is a DistilBERT model trained on 1 million reviews from the yelp open dataset.
It is a regression model, with outputs in the range of ~-2 to ~2. With -2 being 1 star and 2 being 5 stars.
It was trained using the ktrain because of it's ease of use.
tokenizer = AutoTokenizer.from_pretrained( 'distilbert-base-uncased', use_fast=True) model = TFAutoModelForSequenceClassification.from_pretrained( "spentaur/yelp") review = "This place is great!" input_ids = tokenizer.encode(review, return_tensors='tf') pred = model(input_ids).numpy() # pred should === 1.9562385
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