added new function

app.py

@@ -1,4 +1,7 @@
 import gradio as gr
+import transformers
+from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM
+
 title = "Text Summarizer 📝"
 
 
@@ -36,11 +39,32 @@ Abstractive Summarization: The abstractive approach involves rephrasing the comp
 '''
 
 
-interface = gr.Interface.load("huggingface/nikhedward/bart-large-cnn-finetuned-multi-news", 
-  title = title, 
-  description = desc, 
-  theme = "peach", 
-  examples = sample_texts,
-  inputs = gr.inputs.Textbox(lines = 10, label="Input Text"))
 
-interface.launch()
+model_name = 'facebook/bart-large-cnn'
+tokenizer = BartTokenizer.from_pretrained(model_name)
+model = BartForConditionalGeneration.from_pretrained(model_name)
+
+def summarize(inp):
+    inp = inp.replace('\n','')
+    inp = tokenizer.encode(inp, return_tensors='pt', max_length=1024)
+    summary_ids = model.generate(inp, num_beams=4, max_length=150, early_stopping=True)
+    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+    return summary
+
+interface = gr.Interface(fn=summarize, inputs=gr.inputs.Textbox(lines=10, label="Input Text"), description = desc, theme = "peach", examples = sample_texts, title = title outputs="text")
+
+interface.launch()
+
+
+
+
+
+
+#interface = gr.Interface.load("huggingface/nikhedward/bart-large-cnn-finetuned-multi-news", 
+  #title = title, 
+  #description = desc, 
+  #theme = "peach", 
+  #examples = sample_texts,
+  #inputs = gr.inputs.Textbox(lines = 10, label="Input Text"))
+
+#interface.launch()