Update app.py

app.py

@@ -5,34 +5,35 @@ from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
 print("runningg")
 
 
-torch.random.manual_seed(0) 
-model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3-mini-4k-instruct",trust_remote_code=True)
-tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3-mini-4k-instruct") 
-
-text = st.text_area("Enter text....")
-messages = [ 
-    {"role": "system", "content": "You are a helpful AI assistant."}, 
-    {"role": "user", "content": "Can you provide ways to eat combinations of bananas and dragonfruits?"}, 
-    {"role": "assistant", "content": "Sure! Here are some ways to eat bananas and dragonfruits together: 1. Banana and dragonfruit smoothie: Blend bananas and dragonfruits together with some milk and honey. 2. Banana and dragonfruit salad: Mix sliced bananas and dragonfruits together with some lemon juice and honey."}, 
-    {"role": "user", "content": "What about solving an 2x + 3 = 7 equation?"}, 
-] 
-
-
-pipe = pipeline( 
-    "text-generation", 
-    model=model, 
-    tokenizer=tokenizer, 
-) 
-
-generation_args = { 
-    "max_new_tokens": 500, 
-    "return_full_text": False, 
-    "temperature": 0.0, 
-    "do_sample": False, 
-} 
-
-output = pipe(messages, **generation_args) 
-
-if text:
-    out = pipe(text)
-    st.write(out)
+#torch.random.manual_seed(0) 
+#model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3-mini-4k-instruct",trust_remote_code=True)
+#tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3-mini-4k-instruct") 
+
+#text = st.text_area("Enter text....")
+#messages = [ 
+#    {"role": "system", "content": "You are a helpful AI assistant."}, 
+#    {"role": "user", "content": "Can you provide ways to eat combinations of bananas and dragonfruits?"}, 
+#    {"role": "assistant", "content": "Sure! Here are some ways to eat bananas and dragonfruits together: 1. Banana and dragonfruit smoothie: Blend bananas and dragonfruits together with some milk and honey. 2. Banana and dragonfruit salad: Mix sliced bananas and dragonfruits together with some lemon juice and honey."}, 
+#    {"role": "user", "content": "What about solving an 2x + 3 = 7 equation?"}, 
+#] 
+
+
+#pipe = pipeline( 
+#    "text-generation", 
+#    model=model, 
+#    tokenizer=tokenizer, 
+#) 
+
+#generation_args = { 
+#    "max_new_tokens": 500, 
+#    "return_full_text": False, 
+#    "temperature": 0.0, 
+#    "do_sample": False, 
+#} 
+
+#output = pipe(messages, **generation_args) 
+
+#if text:
+#    out = pipe(text)
+#    st.write(out)
+st.write("aaa")