Update app.py

app.py

@@ -96,7 +96,7 @@ def ner(text, labels: str, nested_ner: bool) -> Dict[str, Union[str, int, float]
 with gr.Blocks(title="GLiNER-base") as demo:
     gr.Markdown(
         """
-        # GLiNER-base
+        # GLiNER-Multi
 
         GLiNER is a Named Entity Recognition (NER) model capable of identifying any entity type using a bidirectional transformer encoder (BERT-like). It provides a practical alternative to traditional NER models, which are limited to predefined entities, and Large Language Models (LLMs) that, despite their flexibility, are costly and large for resource-constrained scenarios.