Create app.py

app.py

@@ -0,0 +1,12 @@
+from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
+import gradio as grad
+import ast
+import nltk
+from sentence_transformers import SentenceTransformer, util
+import numpy as np
+
+model = SentenceTransformer('sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2')
+def embed(sentences):
+    reponse = model.encode(sentences)
+    return response
+grad.Interface(embed, inputs=[text"], outputs="text").launch()