Update app.py

app.py

@@ -2,7 +2,7 @@ import streamlit as st
 from transformers import RobertaTokenizer,AutoModelForSequenceClassification
 import torch
 
-state_dict=torch.load("fine_tuned_roberta.bin",map_location=torch.device("cpu"))
+state_dict=torch.load("fine_tuned_roberta_comments.bin",map_location=torch.device("cpu"))
 tokenizer=RobertaTokenizer.from_pretrained("roberta-base")
 model =  AutoModelForSequenceClassification.from_pretrained('roberta-base',
                                                       problem_type="multi_label_classification", 
@@ -26,7 +26,7 @@ def main():
 @st.cache_data
 def get_predictions(title, post, commentaire):
     model.eval()
-    inputs = tokenizer("title of the post: " + title + "\n" + "post: " + post + "\n" + "comment: " + commentaire, return_tensors="pt", padding=True, truncation=True, max_length=512)
+    inputs = tokenizer("comment: " + commentaire, return_tensors="pt", padding=True, truncation=True, max_length=512)
     input_ids = inputs['input_ids'].to(device)
     attention_mask = inputs['attention_mask'].to(device)
     with torch.no_grad():