add distill endpoint

app.py

@@ -13,7 +13,7 @@ HfFolder.save_token(access_token)
 tokenizer_path = "gpt2"
 small_model_path = "hunthinn/movie_title_gpt2_small"
 medium_model_path = "hunthinn/movie_title_gpt2_medium"
-# distill_model_path = "hunthinn/movie_title_gpt2"
+distill_model_path = "hunthinn/movie_title_gpt2"
 
 tokenizer = GPT2Tokenizer.from_pretrained(tokenizer_path)
 small_model = GPT2LMHeadModel.from_pretrained(small_model_path)
@@ -42,7 +42,7 @@ def infer_title_medium(input):
         response = response.split("A:")
         return response[-1]
 
-"""
+
 def infer_title_distill(input):
     if input:
         input_text = "Q: " + input + " A:"
@@ -53,7 +53,7 @@ def infer_title_distill(input):
         response = tokenizer.decode(output[0], skip_special_tokens=True)
         response = response.split("A:")
         return response[-1]
-"""
+
 
 app = Flask(__name__)
 
@@ -70,13 +70,13 @@ def small_model_endpoint(input):
     output = infer_title_small(input)
     return jsonify({"output": output})
 
-'''
+
 @app.route("/distill/<input>")
 def distill_model_endpoint(input):
 
     output = infer_title_distill(input)
     return jsonify({"output": output})
-'''
+
 
 @app.route("/medium/<input>")
 def medium_model_endpoint(input):