Update app.py

app.py

@@ -1,22 +1,19 @@
-from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
-import torch
-
-model_name = "Helsinki-NLP/opus-mt-he-en"
-model_version = "1.0.0"  # Replace with the specific version you want to use
-tokenizer = AutoTokenizer.from_pretrained(model_name, revision=model_version)
-model = AutoModelForSeq2SeqLM.from_pretrained(model_name, revision=model_version)
+from transformers import pipeline
 
 def translate_hebrew_to_english(hebrew_text):
-    inputs = tokenizer.encode(hebrew_text, return_tensors="pt", padding=True)
-    outputs = model.generate(inputs, max_length=128, num_beams=4, early_stopping=True)
-    translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    return translated_text
+    # Load the translation pipeline for Hebrew to English
+    translator = pipeline("translation", model="Helsinki-NLP/opus-mt-he-en")
+
+    # Translate the Hebrew text to English
+    translation = translator(hebrew_text, max_length=512)[0]["translation_text"]
+    
+    return translation
+
+# Prompt the user to input Hebrew text
+hebrew_text = input("Enter the Hebrew text to be translated to English:\n")
 
-def main():
-    hebrew_text = input("Paste the Hebrew text to translate: ")
-    translated_text = translate_hebrew_to_english(hebrew_text)
-    print("Translated text:")
-    print(translated_text)
+# Translate the Hebrew text to English
+english_text = translate_hebrew_to_english(hebrew_text)
 
-if __name__ == "__main__":
-    main()
+# Display the translated text
+print("\nEnglish Translation:\n", english_text)