Update app.py

app.py

@@ -1,7 +1,7 @@
 import torch
-from transformers import AutoTokenizer, TextIteratorStreamer
-# from modeling_nort5 import NorT5ForConditionalGeneration
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, TextIteratorStreamer
 from threading import Thread
+import gradio as gr
 
 
 print(f"Starting to load the model to memory")
@@ -25,14 +25,6 @@ model.eval()
 print(f"Sucessfully loaded the model to the memory")
 
 
-INITIAL_PROMPT = "Du er NorT5, en språkmodell laget ved Universitetet i Oslo. Du er en hjelpsom og ufarlig assistent som er glade for å hjelpe brukeren med enhver forespørsel."
-TEMPERATURE = 0.7
-SAMPLE = True
-BEAMS = 1
-PENALTY = 1.2
-TOP_K = 64
-TOP_P = 0.95
-
 LANGUAGES = [
     "🇬🇧 English",
     "🇳🇴 Norwegian (Bokmål)",
@@ -71,15 +63,9 @@ def switch_inputs(source, target, source_language, target_language):
     return target, source, target_language, source_language
 
 
-import gradio as gr
-
 with gr.Blocks(theme='sudeepshouche/minimalist') as demo:
 
     gr.Markdown("# Norwegian-English translation")
-    # gr.HTML('<img src="https://huggingface.co/ltg/norbert3-base/resolve/main/norbert.png" width=6.75%>')
-    # gr.Checkbox(label="I want to publish all my conversations", value=True)
-
-    # chatbot = gr.Chatbot(value=[[None, "Hei, hva kan jeg gjøre for deg? 😊"]])
 
     with gr.Row():
         with gr.Column(scale=7, variant="panel"):