Update app.py

app.py

@@ -3,13 +3,29 @@ from transformers import BartTokenizer, BartForConditionalGeneration
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelWithLMHead, TranslationPipeline
 
+
+
+from transformers import pipeline
+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('en'))
+    tln=output[0]
+    for item in tln:
+        result=tln[item]
+    return result
+#Gradio Interface
+
+
+
+
 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>'
+def article_summarization(result):
+    input_ =  str(result) + ' </s>'
 # generate summary
-    input_ids = tokenizer.encode(translated_text, return_tensors='pt')
+    input_ids = tokenizer.encode(result, return_tensors='pt')
     summary_ids = model.generate(input_ids,
             min_length=20,
             max_length=12000)