Update app.py

app.py

@@ -2,13 +2,16 @@ import torch
 import gradio as gr
 from transformers import pipeline
 
-# Use the mT5 model for multilingual summarization, including Hebrew
-text_summary = pipeline("summarization", model="csebuetnlp/mT5_multilingual_XLSum", torch_dtype=torch.bfloat16)
+# Use the Dicta IL model for summarization with a manual prompt in Hebrew
+model_name = "dicta-il/dictalm2.0"
+text_summary = pipeline("text2text-generation", model=model_name, torch_dtype=torch.bfloat16)
 
 def summary(input):
+    # Create a prompt in Hebrew for summarization
+    prompt = f"סכם את הטקסט הבא: {input}"
     # Increase max_length and set max_new_tokens to avoid input length issues
-    output = text_summary(input, max_length=512, min_length=30, do_sample=False)
-    return output[0]['summary_text']
+    output = text_summary(prompt, max_length=512, min_length=30, do_sample=False)
+    return output[0]['generated_text']
 
 gr.close_all()