| import sys |
| from transformers import pipeline |
|
|
| |
| candidate_labels_spam = ['Spam', 'not Spam'] |
| candidate_labels_urgent = ['Urgent', 'not Urgent'] |
| model="SpamUrgencyDetection" |
| clf = pipeline("zero-shot-classification", model=model) 32 |
| def predict(text): |
| p_spam = clf(text, candidate_labels_spam)["labels"][0] |
| p_urgent = clf(text, candidate_labels_urgent)["labels"][0] |
| return p_spam,p_urgent |
|
|
|
|
| import pandas as pd |
| df = pd.read_csv("test.csv") |
|
|
| texts=df["text"] |
| for i in range( len(texts)): |
| print(texts[i],predict(texts[i])) |
|
|