use huggingface_hub.model_inifo() to get pipline_tag (#20077)

src/transformers/pipelines/__init__.py

@@ -26,7 +26,7 @@ from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
 
 from numpy import isin
 
-from huggingface_hub.file_download import http_get
+from huggingface_hub import model_info
 
 from ..configuration_utils import PretrainedConfig
 from ..dynamic_module_utils import get_class_from_dynamic_module
@@ -389,25 +389,17 @@ def get_supported_tasks() -> List[str]:
 
 
 def get_task(model: str, use_auth_token: Optional[str] = None) -> str:
-    tmp = io.BytesIO()
-    headers = {}
-    if use_auth_token:
-        headers["Authorization"] = f"Bearer {use_auth_token}"
-
     try:
-        http_get(f"https://huggingface.co/api/models/{model}", tmp, headers=headers)
-        tmp.seek(0)
-        body = tmp.read()
-        data = json.loads(body)
+        info = model_info(model, token=use_auth_token)
     except Exception as e:
         raise RuntimeError(f"Instantiating a pipeline without a task set raised an error: {e}")
-    if "pipeline_tag" not in data:
+    if not info.pipeline_tag:
         raise RuntimeError(
             f"The model {model} does not seem to have a correct `pipeline_tag` set to infer the task automatically"
         )
-    if data.get("library_name", "transformers") != "transformers":
-        raise RuntimeError(f"This model is meant to be used with {data['library_name']} not with transformers")
-    task = data["pipeline_tag"]
+    if getattr(info, "library_name", "transformers") != "transformers":
+        raise RuntimeError(f"This model is meant to be used with {info.library_name} not with transformers")
+    task = info.pipeline_tag
     return task