set pipeline tag in model card

app.py

@@ -2,7 +2,7 @@ import os
 import shutil
 import torch
 import gradio as gr
-from huggingface_hub import HfApi, whoami, ModelCard
+from huggingface_hub import HfApi, whoami, ModelCard, model_info
 from gradio_huggingfacehub_search import HuggingfaceHubSearch
 from textwrap import dedent
 from pathlib import Path
@@ -57,7 +57,7 @@ def export(model_id: str, private_repo: bool, overwritte: bool, oauth_token: gr.
 
         if library_name == "diffusers":
             auto_model_class = "OVDiffusionPipeline"
-        else:
+        elif library_name == "transformers":
             task = TasksManager.infer_task_from_model(model_id, token=oauth_token.token)
 
             if task == "text2text-generation":
@@ -67,7 +67,9 @@ def export(model_id: str, private_repo: bool, overwritte: bool, oauth_token: gr.
                 return f"The task '{task}' is not supported, only {_HEAD_TO_AUTOMODELS.keys()} tasks are supported"
 
             auto_model_class = _HEAD_TO_AUTOMODELS[task]
-
+        else:
+            # TODO: add sentence-transformers and timm support in space
+            return f"Library {library_name} not yet supported"
 
         ov_files = _find_files_matching_pattern(
             model_id,
@@ -129,6 +131,11 @@ def export(model_id: str, private_repo: bool, overwritte: bool, oauth_token: gr.
                 card.data.tags.append("openvino")
                 card.data.tags.append("openvino-export")
                 card.data.base_model = model_id
+
+                pipeline_tag = getattr(model_info(model_id, token=oauth_token.token), "pipeline_tag", None)
+                if pipeline_tag is not None:
+                    card.data.pipeline_tag = pipeline_tag
+
                 card.text = dedent(
                     f"""
                     This model was converted to OpenVINO from [`{model_id}`](https://huggingface.co/{model_id}) using [optimum-intel](https://github.com/huggingface/optimum-intel)