Update app.py

app.py

@@ -1,12 +1,25 @@
-from transformers import pipeline
+import torch
+from transformers import BartTokenizer, BartForConditionalGeneration
 import gradio as gr
-pipe= pipeline('text2text-generation', model="facebook/m2m100_418M")
-def generate_text(inp):
-    output=pipe(inp, forced_bos_token_id=pipe.tokenizer.get_lang_id('fr'))
-    tln=output[0]
-    for item in tln:
-        result=tln[item]
-    return result
-#Gradio Interface
-output_text = gr.outputs.Textbox()
-gr.Interface(generate_text,"textbox", output_text).launch(inline=False)
+from transformers import AutoTokenizer, AutoModelWithLMHead, TranslationPipeline
+
+model = BartForConditionalGeneration.from_pretrained("facebook/bart-large-cnn")
+tokenizer = BartTokenizer.from_pretrained("facebook/bart-large-cnn")
+
+def article_summarization(translated_text):
+    input_ =  str(text) + ' </s>'
+# generate summary
+    input_ids = tokenizer.encode(translated_text, return_tensors='pt')
+    summary_ids = model.generate(input_ids,
+            min_length=20,
+            max_length=12000)
+
+    summary_text = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+    return(summary_text)
+
+
+#iface = gr.Interface(fn=article_summarization,title="Summarization in English",description="facebook/bart-large-cnn for summarization in English", inputs=(lines=50,['text']), outputs=["text"])
+
+iface = gr.Interface(fn=article_summarization,title="Summarization in English",description="facebook/bart-large-cnn for summarization in English", inputs=gr.inputs.Textbox(lines=50, placeholder="Enter newpaper article to be summarized"), outputs=["text"])
+
+iface.launch()