added file

app.py

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+from transformers import pipeline
+import gradio as gr
+
+
+
+ner = pipeline("ner",
+               model='kaiku03/bert-base-NER-finetuned_custom_complain_dataset_NER9',
+              #  grouped_entities=True,
+               aggregation_strategy="simple"
+               )
+
+
+# function for the gradio app
+def fn_ner(prompt):
+    return ner(prompt)
+
+
+# gradio app
+# Define example inputs and outputs
+examples = [
+    "Subject: Defective Date: 08-13-2023 Product: XXX speaker Location: 456 Sound Avenue, Audiotown",
+    "Subject: Dirty Date: 08-10-2023 Product: UVW Television Location: 567 Willow Lane, Mediatown",
+    "Subject: Missing Parts Date: 08-10-2023 Product: XXX Furniture Set Location: 1800 Antipolo Rizal Furnitown",
+]
+
+iface = gr.Interface(
+    fn=fn_ner,
+    inputs='text',
+    outputs=gr.Label(label="Name Entity Recognition"),
+    examples=[
+        [ex] for ex in examples
+    ],
+    title='English to Tagalog translator',
+    description='This demo performs language translation from English to Tagalog.',
+    article='All done by Kaiku',
+)
+
+iface.launch()

requirements.txt

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+transformers
+gradio==3.40
+torch
+seqeval 
+evaluate