Create load.py

load.py

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+import torch
+from torch.utils.data import Dataset
+import pandas as pd
+from sklearn.model_selection import train_test_split
+from sklearn.metrics import classification_report
+from transformers import RobertaTokenizer, RobertaForSequenceClassification, Trainer, TrainingArguments
+from transformers import TrainerCallback
+import os
+from transformers import TrainingArguments, Trainer
+
+model = RobertaForSequenceClassification.from_pretrained("./best_model")
+tokenizer = RobertaTokenizer.from_pretrained("./best_model")
+
+
+def maliciousornot(link):
+    inputs = tokenizer(link, return_tensors="pt")
+    outputs = model(**inputs)
+    predictions = torch.argmax(outputs.logits, dim=-1)
+    return predictions