Update app.py

app.py

@@ -26,22 +26,11 @@ def log(msg):
 def get_model_size_in_gb(model_name):
     """估算模型大小（以GB为单位）"""
     try:
-        config = AutoConfig.from_pretrained(model_name)
-        num_params = config.num_parameters if hasattr(config, 'num_parameters') else None
-        
-        if num_params is None:
-            # 手动计算参数量
-            if hasattr(config, 'num_hidden_layers') and hasattr(config, 'hidden_size'):
-                # 简单估算，可能不够准确
-                num_params = config.num_hidden_layers * config.hidden_size * config.hidden_size * 4
+        # get model size from huggingface
+        api = HfApi()
+        model_info = api.model_info(model_name)
+        return model_info.safetensors.total / (1024 ** 3)
         
-        if num_params:
-            # 每个参数占用2字节（float16）
-            size_in_gb = (num_params * 2) / (1024 ** 3)
-            return size_in_gb
-        else:
-            # 如果无法计算，返回一个保守的估计
-            return 1  # bypass memory check
     except Exception as e:
         log(f"无法估算模型大小: {str(e)}")
         return 1  # bypass memory check
@@ -98,6 +87,11 @@ def setup_environment(model_name, hf_token):
 def create_hf_repo(repo_name, hf_token, private=True):
     """创建HuggingFace仓库"""
     try:
+        # check if repo already exists
+        api = HfApi()
+        if api.repo_exists(repo_name):
+            log(f"仓库已存在: {repo_name}")
+            return ValueError(f"仓库已存在: {repo_name}, 请使用其他名称或删除已存在的仓库")
         repo_url = create_repo(repo_name, private=private, token=hf_token)
         log(f"创建仓库成功: {repo_url}")
         return repo_url