hello world

question_paper.py

@@ -12,22 +12,22 @@ TOKENIZER = None
 # ?input=%22Name%203%20shows%22
 @app.get("/")
 def llama(input):
-    prompt = [{'role': 'user', 'content': ""+input}]
-    inputs = TOKENIZER.apply_chat_template( prompt, add_generation_prompt=True,     return_tensors='pt' )
+    # prompt = [{'role': 'user', 'content': ""+input}]
+    # inputs = TOKENIZER.apply_chat_template( prompt, add_generation_prompt=True,     return_tensors='pt' )
 
-    tokens = MODEL.generate( inputs.to(MODEL.device), max_new_tokens=1024, temperature=0.3, do_sample=True)
+    # tokens = MODEL.generate( inputs.to(MODEL.device), max_new_tokens=1024, temperature=0.3, do_sample=True)
 
-    tresponse = TOKENIZER.decode(tokens[0], skip_special_tokens=False)
-    print(tresponse)
+    # tresponse = TOKENIZER.decode(tokens[0], skip_special_tokens=False)
+    # print(tresponse)
 
-    return tresponse
+    return "hello world"
 
-@app.on_event("startup")
-def init_model():
-    global MODEL
-    global TOKENIZER
-    if not MODEL:
-        print("loading model")
-        TOKENIZER = AutoTokenizer.from_pretrained('stabilityai/stablelm-zephyr-3b')
-        MODEL = AutoModelForCausalLM.from_pretrained('stabilityai/stablelm-zephyr-3b', device_map="auto")
-        print("loaded model")
+# @app.on_event("startup")
+# def init_model():
+#     global MODEL
+#     global TOKENIZER
+#     if not MODEL:
+#         print("loading model")
+#         TOKENIZER = AutoTokenizer.from_pretrained('stabilityai/stablelm-zephyr-3b')
+#         MODEL = AutoModelForCausalLM.from_pretrained('stabilityai/stablelm-zephyr-3b', device_map="auto")
+#         print("loaded model")