Update app.py

app.py

@@ -1,17 +1,26 @@
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+from transformers import AutoTokenizer, AutoModelWithLMHead
 import gradio as gr
 
 model_name = "deep-learning-analytics/wikihow-t5-small"
-model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
-text2text_tokenizer = AutoTokenizer.from_pretrained(model_name)
+text2text_token = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelWithLMHead.from_pretrained(model_name)
 
-def text2text(paragraph):
-    text = paragraph.strip().replace("\n", "")
-    token_text = text2text_tokenizer.encode(text, return_tensors="pt")
-    token_ids = model.generate(token_text, max_length=250, num_beams=5, repetition_penality=2.5, early_stopping=True)
-    response = text2text_tokenizer.decode(token_ids[0], skip_special_tokens=True) 
+def text2text_summary(para):
+    initial_text = para.strip().replace("\n","")
+    token_text = text2text_token.encode(initial_text, return_tensors="pt")
+
+    token_ids = model.generate(
+            token_text,
+            max_length=250, 
+            num_beams=5,
+            repetition_penalty=2.5, 
+            early_stopping=True
+        )
+
+    response = text2text_token.decode(token_ids[0], skip_special_tokens=True)
     return response
 
+# UX
 in_para = gr.Textbox(lines=10, label="Paragraph", placeholder="Copy paragraph")
 out = gr.Textbox(lines=1, label="Summary")
-gr.Interface(text2text, inputs=in_para, outputs=out)
+gr.Interface(text2text_summary, inputs=in_para, outputs=out).launch()