Update app.py

app.py

@@ -1,12 +1,20 @@
-from transformers import pipeline
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 import gradio as gr
 
-def get_summary(text):
-    summarizer = pipeline("summarization", model="paulowoicho/t5-podcast-summarisation", tokenizer="paulowoicho/t5-podcast-summarisation")
-    summary = summarizer(text, min_length=39, max_length=25000)
-    return summary[0]['summary_text']
+model_name = "EleutherAI/gpt-3.5-turbo"
 
-#gr.Interface(fn=get_summary, inputs="text",  outputs="text").launch()
-gr.Interface.load("models/paulowoicho/t5-podcast-summarisation").launch()
+def summarize_text(input_text):
+    # Load the tokenizer and model
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
 
+    # Tokenize the input text
+    input_ids = tokenizer.encode(input_text, truncation=True, padding=True, return_tensors="pt")
 
+    # Generate the summary
+    summary_ids = model.generate(input_ids, max_length=150, num_beams=2, early_stopping=True)
+    summary = tokenizer.decode(summary_ids.squeeze(), skip_special_tokens=True)
+
+    return summary
+
+gr.Interface(fn=summarize_text, inputs='text', outputs='text').launch()