rephrase export steps

app.py

@@ -18,7 +18,7 @@ if HF_TOKEN:
     repo = Repository(local_dir=DATA_DIR, clone_from=DATASET_REPO_URL, token=HF_TOKEN)
 
 
-def export(token: str, model_id: str, task: str) -> str:
+def export(token: str, model_id: str, task: str = "auto") -> str:
     if token == "" or model_id == "":
         return """
         ### Invalid input 🐞
@@ -78,24 +78,22 @@ TITLE = """
     "
 >
 <h1 style="font-weight: 900; margin-bottom: 10px; margin-top: 10px;">
-    Export your model to OpenVINO with Optimum Intel
+    Export your model to OpenVINO
 </h1>
 </div>
 """
 
 DESCRIPTION = """
-This Space allows you to automatically export your model to the OpenVINO format.
+This Space uses [Optimum Intel](https://huggingface.co/docs/optimum/intel/inference) to automatically export your model to the OpenVINO format.
 
 To export your model you need:
 - A read-access token from [https://huggingface.co/settings/tokens](https://huggingface.co/settings/tokens).
- Read access is enough given that we will open a PR against the source repo.
-- A model id of the model you'd like to export (for example: [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english))
-- A [task](https://huggingface.co/docs/optimum/main/en/exporters/task_manager#pytorch) that will be used to load the model before exporting it. If set to "auto", the task will be automatically inferred. 
+- A  model id from the Hub (for example: [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english))
+
 
 That's it ! 🔥
 
 After the model conversion, we will open a PR against the source repo.
-You will then be able to load the resulting model and run inference using [Optimum Intel](https://huggingface.co/docs/optimum/intel/inference).
 """
 
 with gr.Blocks() as demo:
@@ -116,18 +114,13 @@ with gr.Blocks() as demo:
                 label="Model name",
                 placeholder="distilbert-base-uncased-finetuned-sst-2-english",
             )
-            input_task = gr.Textbox(
-                value="auto",
-                max_lines=1,
-                label='Task (can be left to "auto", will be automatically inferred)',
-            )
 
             btn = gr.Button("Export")
             output = gr.Markdown(label="Output")
 
     btn.click(
         fn=export,
-        inputs=[input_token, input_model, input_task],
+        inputs=[input_token, input_model],
         outputs=output,
     )