1

main.py

@@ -43,29 +43,31 @@ def model_init():
     logging.info(C("[INFO] "f"Model init success!"))
     return tokenizer, model
 
-tokenizer, model = model_init()
-st.balloons()
+# 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()
+# 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()
+#     # =================== 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()
+
+st.snow()