exact_data2023/application/functions/sentiment.py

from transformers import AutoTokenizer
from transformers import pipeline

model = 'application/models/sentiment_model'
tokenizer = AutoTokenizer.from_pretrained('application/tokenizers/sentiment_tokenizer')
# tokenizer = AutoTokenizer.from_pretrained("sdadas/polish-gpt2-small")

def sentiment_prediction(data):
    pipe = pipeline('text-classification', model=model, tokenizer = tokenizer)
    result = pipe(data)
    
    return result

def count_predictions(predictions):
    l0 = 0
    l1 = 0
    l2 = 0
    all = {}

    for i in predictions:
        if i['label'] == 'LABEL_0':
            l0 += 1
        if i['label'] == 'LABEL_1':
            l1 += 1
        if i['label'] == 'LABEL_2':
            l2 += 1

    all['positive'] = l1
    all['negative'] = l0
    all['neutral'] = l2

    return all