Update app.py

app.py

@@ -1,5 +1,7 @@
+!pip install torch
+
 import streamlit as st
-from transformers import pipeline, TFAutoModelForSequenceClassification, AutoTokenizer, TFAutoModelForTokenClassification
+from transformers import pipeline, AutoModelForSequenceClassification, AutoTokenizer, AutoModelForTokenClassification
 from datasets import load_dataset
 import pandas as pd
 
@@ -43,15 +45,16 @@ elif input_method == "Yeni Metin Yaz veya Yapıştır":
 # Model ve tokenizer'ı yükleme
 @st.cache_resource
 def set_model(model_checkpoint):
-    sentiment_model = TFAutoModelForSequenceClassification.from_pretrained(model_checkpoint, from_tf=True)
+    # PyTorch tabanlı modelleri kullan
+    model = AutoModelForSequenceClassification.from_pretrained(model_checkpoint)
     tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
     
     # Named Entity Recognition (NER) için model
-    ner_model = TFAutoModelForTokenClassification.from_pretrained('dbmdz/bert-large-cased-finetuned-conll03-english', from_tf=True)
+    ner_model = AutoModelForTokenClassification.from_pretrained('dbmdz/bert-large-cased-finetuned-conll03-english')
     ner_tokenizer = AutoTokenizer.from_pretrained('dbmdz/bert-large-cased-finetuned-conll03-english')
     
     return {
-        'sentiment_pipeline': pipeline('sentiment-analysis', model=sentiment_model, tokenizer=tokenizer),
+        'sentiment_pipeline': pipeline('sentiment-analysis', model=model, tokenizer=tokenizer),
         'ner_pipeline': pipeline('ner', model=ner_model, tokenizer=ner_tokenizer)
     }