add gradio demo server

classifiers/requirements.txt

@@ -1,4 +1,5 @@
 datasets
 transformers
 evaluate
-torch
+torch
+gradio

classifiers/src/demo.py

@@ -0,0 +1,20 @@
+from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
+import gradio as gr
+
+
+def load_model() -> 'AutoModelForSequenceClassification':
+    """ Load Endian Classifier Model """
+    model_name = "ryfye181/distilbert_endian_classifier"
+    return AutoModelForSequenceClassification.from_pretrained(model_name)
+
+def load_tokenizer() -> 'AutoTokenizer':
+    """ Load Tokenizer """
+    model_name = "ryfye181/distilbert_endian_classifier"
+    return AutoTokenizer.from_pretrained(model_name)
+
+if __name__ == '__main__':
+
+    pipe = pipeline("text-classification", model=load_model(), tokenizer=load_tokenizer())
+
+    demo = gr.Interface().from_pipeline(pipe)
+    demo.launch()