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# -*- coding: utf-8 -*-
"""
Spyder Editor
This is a temporary script file.
"""
from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
import torch
tokenizer = AutoTokenizer.from_pretrained("nomsgadded/opt_RestaurantReview")
model = AutoModelForSequenceClassification.from_pretrained("nomsgadded/opt_RestaurantReview", num_labels=9)
prefix = "##Rating: "
text1 = "Bad"
text2 = "It was really nice to dine there, however the waiter is very mean."
text3 = "Nice"
def inference(text):
text = prefix + text
inputs = tokenizer(text, return_tensors="pt")
classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)
with torch.no_grad():
logits = model(**inputs).logits
predicted_class_id = logits.argmax().item()
print((predicted_class_id+2)/2)
inference(text1)
inference(text2)
inference(text3) |