1 model

app.py

@@ -98,16 +98,19 @@ def side_bar():
             )
 
             summarizer_type = st.selectbox(
-                "Summarizer Type for Long Text", options=["Map Reduce", "Refine"]
+                "Summarizer Type for Long Text", 
+                # options=["Map Reduce", "Refine"]
+                options=["Map Reduce"]
             )
 
             submitted = st.form_submit_button(
                 "Save Parameters",
                 # on_click=update_parameters_change
+                disabled = True
                 )
        
-            if submitted:
-                parameters_change_button(model_name, summarizer_type)
+            # if submitted:
+            #     parameters_change_button(model_name, summarizer_type)
 
 
         st.markdown("\n")
@@ -149,7 +152,13 @@ def side_bar():
 def load_app():
     st.title("Text Summarizer 📝")
 
-    inp_text = st.text_input("Enter text or a url here")
+    # inp_text = st.text_input("Enter text or a url here")
+    # inp_text = st.text_input(
+    #     "Enter text or a url here"
+    # )
+    inp_text = st.text_area(
+        "Enter text here"
+    )
     st.markdown(
         "<h4 style='text-align: center; color: green;'>OR</h4>",
         unsafe_allow_html=True,

config.py

@@ -1,6 +1,6 @@
 MODELS = {
-    "long-t5 v0":"IronOne-AI-Labs/long-t5-tglobal-16k-annual-reports-v0",
+    # "long-t5 v0":"IronOne-AI-Labs/long-t5-tglobal-16k-annual-reports-v0",
     "long-t5 v1":"IronOne-AI-Labs/long-t5-tglobal-16k-annual-reports-v1",
-    "pegasus-x-large v1" : "IronOne-AI-Labs/pegasus-x-large-annual-report-QLoRA-fine-tuned-v1.1", #for tokenizer
-    "openai" : "IronOne-AI-Labs/pegasus-x-large-annual-report-QLoRA-fine-tuned-v1.1"
+    # "pegasus-x-large v1" : "IronOne-AI-Labs/pegasus-x-large-annual-report-QLoRA-fine-tuned-v1.1", #for tokenizer
+    # "openai" : "IronOne-AI-Labs/pegasus-x-large-annual-report-QLoRA-fine-tuned-v1.1"
 }

model.py

@@ -8,9 +8,9 @@ import streamlit as st
 import torch
 
 load_dotenv()
-hf_token = os.environ.get("HF_TOKEN")
-# hf_token = st.secrets["HF_TOKEN"]
-login(token=hf_token)
+# hf_token = os.environ.get("HF_TOKEN")
+# # hf_token = st.secrets["HF_TOKEN"]
+# login(token=hf_token)
 logger = getLogger(__name__)
 device = "cuda" if torch.cuda.is_available() else "cpu"