Upload README.md

README.md

@@ -34,15 +34,12 @@ This model can be utilized for various NLP tasks such as text generation, summar
 
     import os
     import requests
-    import shutil
     from transformers import GPT2LMHeadModel
     from cryptography.fernet import Fernet
-
     os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
 
-    print("\nDownload Serbian-GPT-2 model...")
-
     # Download Serbian-GPT-2 model
+    print("\nDownload Serbian-GPT-2 model...")
     model_name = 'edukom/Serbian-GPT-2'
     base_url = f'https://huggingface.co/{model_name}/resolve/main/'
     files_to_download = ['added_tokens.json', 'config.json', 'generation_config.json', 'merges.txt', 'pytorch_model.bin', 'special_tokens_map.json', 'tokenizer.json', 'tokenizer_config.json', 'vocab.json']
@@ -69,18 +66,8 @@ 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)
 
-        source_path = os.path.join(cache_dir, 'pytorch_model.bin')
-
-        destination_dir = os.path.join(cache_dir, 'models--edukom--Serbian-GPT-2', 'snapshots', '33f6d75d2eaa3479a83a7d5c2bdb29cebff58a4d')
-        os.makedirs(destination_dir, exist_ok=True)
-
-        destination_path = os.path.join(destination_dir, 'pytorch_model.bin')
-
-        shutil.copyfile(source_path, destination_path)
-
         # Loading Serbian-GPT-2 model
-        model = GPT2LMHeadModel.from_pretrained(model_name, cache_dir=cache_dir)
-
+        model = GPT2LMHeadModel.from_pretrained(cache_dir)
         print("\nCongratulations, the Serbian-GPT-2 model is ready for use ヅ\n")
 
     except Exception as e: