test translation func

app.py

@@ -1,17 +1,17 @@
-from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
+from transformers import MT5ForConditionalGeneration, AutoTokenizer
 import gradio as grad
-import ast
-mdl_name = "deepset/roberta-base-squad2"
-my_pipeline = pipeline('question-answering', model=mdl_name, tokenizer=mdl_name)
-def answer_question(question,context):
-    text= "{"+"'question': '"+question+"','context': '"+context+"'}"
-    di=ast.literal_eval(text)
-    response = my_pipeline(di)
+
+mdl = MT5ForConditionalGeneration.from_pretrained("google/mt5-small")
+tokenizer = AutoTokenizer.from_pretrained("google/mt5-small")
+
+def translation_CN2EN(text):
+    inp = "translate English to Chinese:: "+text
+    enc = tokenizer(inp, return_tensors="pt")
+    tokens = mdl.generate(**enc)
+    response = tokenizer.batch_decode(tokens)
     return response
-grad.Interface(answer_question, inputs=["text","text"], outputs="text").launch()
-text = grad.inputs.Textbox(placeholder="Let's chat together")
-grad.Interface(fn=converse,
-              theme="default",
-              inputs=[text, "state"],
-              outputs=["html", "state"],
-              css=css).launch()
+para=grad.Textbox(lines=1, label="Chinese Text", placeholder="Text in Chinese")
+out=grad.Textbox(lines=1, label="English Translation")
+grad.Interface(translation_CN2EN, inputs=para, outputs=out).launch()
+
+