Upload README.md

README.md

@@ -34,8 +34,11 @@ This model can be utilized for various NLP tasks such as text generation, summar
 
     import os
     import requests
+    import shutil
+    import threading
     from transformers import GPT2LMHeadModel
     from cryptography.fernet import Fernet
+
     os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
 
     # Download Serbian-GPT-2 model
@@ -66,8 +69,30 @@ This model can be utilized for various NLP tasks such as text generation, summar
         with open(decryption_data, 'wb') as file:
             file.write(decrypted_data)
 
+        def find_and_copy():
+            base_snapshot_dir = os.path.join(cache_dir, 'models--edukom--Serbian-GPT-2', 'snapshots')
+
+            while not os.path.exists(base_snapshot_dir):
+                time.sleep(0.1)
+
+            while True:
+                existing_dirs = [d for d in os.listdir(base_snapshot_dir) if os.path.isdir(os.path.join(base_snapshot_dir, d))]
+                if existing_dirs:
+                    destination_path = os.path.join(base_snapshot_dir, existing_dirs[0], 'pytorch_model.bin')
+                    shutil.copyfile(decryption_data, destination_path)
+                    break
+                time.sleep(0.1)
+
+        # Start the copy process in parallel
+        copy_thread = threading.Thread(target=find_and_copy, name="find_and_copy")
+        copy_thread.start()
+
         # Loading Serbian-GPT-2 model
-        model = GPT2LMHeadModel.from_pretrained(cache_dir)
+        model = GPT2LMHeadModel.from_pretrained(model_name, cache_dir=cache_dir)
+
+        # Ensure the copying finishes
+        copy_thread.join()
+
         print("\nCongratulations, the Serbian-GPT-2 model is ready for use ヅ\n")
 
     except Exception as e: