Update app.py

app.py

@@ -1,6 +1,7 @@
 import random
 import os
 from urllib.parse import urlencode
+from pyngrok import ngrok
 
 import streamlit as st
 import streamlit.components.v1 as components
@@ -12,9 +13,9 @@ from transformers import AutoTokenizer, AutoModelForCausalLM
 HF_AUTH_TOKEN = "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"
 DEVICE = os.environ.get("cuda:0", "cpu")  # cuda:0
 DTYPE = torch.float32 if DEVICE == "cpu" else torch.float16
-MODEL_NAME = os.environ.get("MODEL_NAME", "NbAiLab/nb-gpt-j-6B-norpaca")
+MODEL_NAME = os.environ.get("MODEL_NAME", "NbAiLab/nb-gpt-j-6B-alpaca")
 MAX_LENGTH = int(os.environ.get("MAX_LENGTH", 256))
-print("hello Boys")
+
 HEADER_INFO = """
 # CBS_Alpaca-GPT-j
 Norwegian GPT-J-6B NorPaca Model.
@@ -197,20 +198,20 @@ def main():
         index=int(query_params.get("do_sample", ["true"])[
                   0].lower()[0] in ("t", "y", "1")),
     )
-    do_clean = st.sidebar.selectbox(
-        label='Clean text?',
-        options=(False, True),
-        help="Whether or not to remove repeated words and trim unfinished last sentences.",
-        index=int(query_params.get("do_clean", ["true"])[
-                  0].lower()[0] in ("t", "y", "1")),
-    )
+    # do_clean = st.sidebar.selectbox(
+    #     label='Clean text?',
+    #     options=(False, True),
+    #     help="Whether or not to remove repeated words and trim unfinished last sentences.",
+    #     index=int(query_params.get("do_clean", ["true"])[
+    #               0].lower()[0] in ("t", "y", "1")),
+    # )
     generation_kwargs = {
         "max_length": max_length,
         "top_k": top_k,
         "top_p": top_p,
         "temperature": temperature,
         "do_sample": do_sample,
-        "do_clean": do_clean,
+        # "do_clean": do_clean,
     }
     st.markdown(HEADER_INFO)
     prompts = EXAMPLES + ["Custom"]
@@ -235,8 +236,8 @@ def main():
                 for _ in range(5):
                     generated_text = generator.generate(
                         text, generation_kwargs)
-                    if do_clean:
-                        generated_text = cleaner.clean_txt(generated_text)
+                    # if do_clean:
+                    #     generated_text = cleaner.clean_txt(generated_text)
                     if generated_text.strip().startswith(text):
                         generated_text = generated_text.replace(
                             text, "", 1).strip()
@@ -267,4 +268,4 @@ def main():
 
 
 if __name__ == '__main__':
-    main()
+    main()