balloons debug

main.py

@@ -2,6 +2,7 @@
 import os, logging, torch, streamlit as st
 from transformers import (
     AutoTokenizer, AutoModelForCausalLM)
+st.balloons()
 
 # --------------------- HELPER --------------------- #
 def C(text, color="yellow"):
@@ -17,12 +18,14 @@ def C(text, color="yellow"):
     return (
         f"{color_dict.get(color, None)}"
         f"{text}{color_dict[None]}")
+st.balloons()
 
 # ------------------ ENVIORNMENT ------------------- #
 os.environ["HF_ENDPOINT"] = "https://huggingface.co"
 device = ("cuda" 
     if torch.cuda.is_available() else "cpu")
 logging.info(C("[INFO] "f"device = {device}"))
+st.balloons()
 
 # ------------------ INITITALIZE ------------------- #
 @st.cache
@@ -41,20 +44,28 @@ def model_init():
     return tokenizer, model
 
 tokenizer, model = model_init()
+st.balloons()
 
 try:
     # ===================== INPUT ====================== #
     # prompt = "\u554F\uFF1A\u53F0\u7063\u6700\u9AD8\u7684\u5EFA\u7BC9\u7269\u662F\uFF1F\u7B54\uFF1A"  #@param {type:"string"}
     prompt = st.text_input("Prompt: ")
+    st.balloons()
+    
 
     # =================== INFERENCE ==================== #
     if prompt:
+        st.balloons()
         with torch.no_grad():
             [texts_out] = model.generate(
                 **tokenizer(
                     prompt, return_tensors="pt"
                 ).to(device))
+        st.balloons()
         output_text = tokenizer.decode(texts_out)
+        st.balloons()
         st.markdown(output_text)
+        st.balloons()
 except Exception as err:
     st.write(str(err))
+    st.snow()