| from transformers import pipeline, AutoModelForTokenClassification, AutoTokenizer | |
| model= transformers.AutoModelForSequenceClassification.from_pretrained(".") | |
| tokenizer=transformers.AutoTokenizer.from_pretrained(".") | |
| dosya=["dvd.tsv","Books.tsv","Kitchen.tsv","electronics.tsv"][3] | |
| data = [line.strip().split("\t") for line in open(dosya)] | |
| sa= pipeline("sentiment-analysis", model=model, tokenizer=tokenizer) | |
| real=[d[1] for d in data] | |
| pred=[sa(d[0]) for d in data] | |
| pred2=[p[0]['label'].split("_")[1] for p in pred] | |
| res=[a==b for (a,b) in zip(pred2, real)] | |
| sum(res)/len(res) | |