Update app.py

app.py

@@ -1,25 +1,18 @@
-from transformers import AutoTokenizer, AutoModelWithLMHead
+from transformers import T5ForConditionalGeneration, T5Tokenizer
 import gradio as grad
-text2text_tkn = AutoTokenizer.from_pretrained("deep-learning-analytics/wikihow-t5-small")
-mdl = AutoModelWithLMHead.from_pretrained("deep-learning-analytics/wikihow-t5-small")
 
+text2text_tkn= T5Tokenizer.from_pretrained("t5-small")
+mdl = T5ForConditionalGeneration.from_pretrained("t5-small")
 
-def text2text_summary(para):
-    initial_txt = para.strip().replace("\n","")
-    tkn_text = text2text_tkn.encode(initial_txt, return_tensors="pt")
 
-    tkn_ids = mdl.generate(
-            tkn_text,
-            max_length=250, 
-            num_beams=5,
-            repetition_penalty=2.5, 
-           
-            early_stopping=True
-        )
 
-    response = text2text_tkn.decode(tkn_ids[0], skip_special_tokens=True)
-    return response
+def text2text_translation(text):
+     inp = "translate English to German:: "+text
+     enc = tokenizer(inp, return_tensors="pt")
+     tokens = mdl.generate(**enc)
+     response=text2text_tkn.batch_decode(tokens)
+     return response
 
-para=grad.Textbox(lines=10, label="Paragraph", placeholder="Copy paragraph")
-out=grad.Textbox(lines=1, label="Summary")
-grad.Interface(text2text_summary, inputs=para, outputs=out).launch()
+para=grad.Textbox(lines=10, label="English Text", placeholder="Text in English")
+out=grad.Textbox(lines=1, label="German Translation")
+grad.Interface(text2text_translation, inputs=para, outputs=out).launch()