add files

.gitignore

@@ -0,0 +1,2 @@
+dev.py
+env/

README.md

@@ -1,3 +1,17 @@
 ---
 license: apache-2.0
 ---
+This model is 👇
+
+        ███████╗ ██████╗   █████╗  ██████╗  ███████╗ ███████╗
+        ██╔════╝ ██╔══██╗ ██╔══██╗ ██╔══██╗  ██╔════╝ ██╔════╝
+        ███████╗ ██████╔╝ ███████║ ██████╔╝  ███████╗ █████╗  
+        ╚════██║ ██╔═══╝  ██╔══██║ ██╔══██╗ ╚════██║█ █╔══╝  
+        ███████║ ██║      ██║  ██║ ██║  ██ ║███████║ ███████╗
+        ╚══════╝ ╚═╝      ╚═╝  ╚═╝ ╚═╝  ╚═ ╝╚══════╝ ╚══════╝
+                                                                                                         
+![Alt Text](https://media.giphy.com/media/4Hmjz2sqdtASJ2gFMH/giphy.gif)
+̷͈̍
+̵̳͒R̶̙̓i̸̟͘c̴̻̆k̸̑͜ÿ̷̳́
+̸̪̚
+̷͖̀

handler.py

@@ -0,0 +1,23 @@
+from typing import Dict, Any
+from deepsparse import Pipeline
+from time import perf_counter
+
+class EndpointHandler:
+
+    def __init__(self, path=""):
+
+        self.pipeline = Pipeline.create(task="text-classification", model_path=path)
+
+    def __call__(self, data: Dict[str, Any]) -> Dict[str, str]:
+        """
+        Args:
+            data (:obj:): prediction input text
+        """
+        inputs = data.pop("inputs", data)
+
+        start = perf_counter()
+        prediction = self.pipeline(inputs)
+        end = perf_counter()
+        delta = end - start
+
+        return prediction.json(), "latency: " + str(delta) + " secs."

requirements.txt

@@ -0,0 +1 @@
+deepsparse>=1.2.0