Update app.py

app.py

@@ -1,9 +1,23 @@
 import streamlit as st
 import torch
 import os
+import requests
+
+# Define the URL of your model file
+model_url = "https://huggingface.co/SLPG/English_to_Urdu_Unsupervised_MT/resolve/main/checkpoint_8_96000.pt"
+model_path = "checkpoint_8_96000.pt"
+
+# Define a function to download the model file
+def download_model(url, file_path):
+    if not os.path.exists(file_path):
+        with requests.get(url, stream=True) as r:
+            r.raise_for_status()
+            with open(file_path, 'wb') as f:
+                for chunk in r.iter_content(chunk_size=8192):
+                    f.write(chunk)
+    return file_path
 
 # Load the model checkpoint
-model_path = "https://huggingface.co/SLPG/English_to_Urdu_Unsupervised_MT/tree/main/checkpoint_8_96000.pt"
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
 # Define a function to load the model
@@ -25,10 +39,13 @@ def translate(model, input_text, src_dict, tgt_dict):
     translated_text = "Translated text here"
     return translated_text
 
+# Download the model file
+download_model(model_url, model_path)
+
 # Load model and dictionaries
 model = load_model(model_path)
-src_dict = load_dictionary("SLPG/English_to_Urdu_Unsupervised_MT/dict.en.txt")
-tgt_dict = load_dictionary("SLPG/English_to_Urdu_Unsupervised_MT/dict.ur.txt")
+src_dict = load_dictionary("path/to/dict.en.txt")
+tgt_dict = load_dictionary("path/to/dict.ur.txt")
 
 # Streamlit interface
 st.title("Translation Model Inference")