Update app.py

app.py

@@ -1,33 +1,23 @@
 import torch
 import gradio as gr
-
-# Use a pipeline as a high-level helper
 from transformers import pipeline
 
-# text_summary = pipeline("summarization", model="dicta-il/dictalm2.0", torch_dtype=torch.bfloat16)
+# Use the mT5 model for multilingual summarization, including Hebrew
 text_summary = pipeline("summarization", model="csebuetnlp/mT5_multilingual_XLSum", torch_dtype=torch.bfloat16)
 
-
-
-
-# text='''Elon Reeve Musk (/ˈiːlɒn/ EE-lon; born June 28, 1971) is a businessman and investor.
-# He is the founder, chairman, CEO, and CTO of SpaceX; angel investor, CEO, product architect,
-# and former chairman of Tesla, Inc.; owner, executive chairman, and CTO of X Corp.;
-# founder of the Boring Company and xAI; co-founder of Neuralink and OpenAI; and president
-# of the Musk Foundation. He is one of the wealthiest people in the world; as of April 2024,
-# Forbes estimates his net worth to be $178 billion.[4]'''
-# print(text_summary(text));
-
-def summary (input):
-    output = text_summary(input)
+def summary(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']
 
 gr.close_all()
 
-# demo = gr.Interface(fn=summary, inputs="text",outputs="text")
-demo = gr.Interface(fn=summary,
-                    inputs=[gr.Textbox(label="Input text to summarize",lines=6)],
-                    outputs=[gr.Textbox(label="Summarized text",lines=4)],
-                    title="Hebrew Text Summarizer",
-                    description="This application will summarize Hebrew text.")
-demo.launch()
+demo = gr.Interface(
+    fn=summary,
+    inputs=[gr.Textbox(label="Input text to summarize", lines=6)],
+    outputs=[gr.Textbox(label="Summarized text", lines=4)],
+    title="Hebrew Text Summarizer",
+    description="This application will summarize Hebrew text."
+)
+
+demo.launch()