Update app.py

app.py

@@ -11,22 +11,22 @@ model = AutoModelForSeq2SeqLM.from_pretrained(SAVED_MODEL_PATH).to(device)
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 
 dataset = load_dataset("samsum")
+#dataset = load_dataset("samsum", download_mode="force_redownload")
+
 
 train_data = dataset["train"]
 validation_data = dataset["validation"] 
 test_data = dataset["test"]
 
-def summarize(tokenizer, model, text):
+def summarize(text):
     inputs = tokenizer(f"Summarize dialogue >>\n {text}", return_tensors="pt", max_length=1000, truncation=True, padding="max_length").to(device)
     summary_ids = model.generate(inputs.input_ids, num_beams=4, max_length=100, early_stopping=True)
     summary = [tokenizer.decode(g, skip_special_tokens=True, clean_up_tokenization_spaces=False) for g in summary_ids]
     return summary[0]
 
-def summarize_dialogue(text):
-    return summarize(tokenizer, model, text)
 
 iface = gr.Interface(
-    fn=summarize_dialogue,
+    fn=summarize,
     inputs=gr.inputs.Textbox(lines=10, label="Input Dialogue"),
     outputs=gr.outputs.Textbox(label="Generated Summary")
 )