add markdown to gradio

gradio_ner.py

@@ -84,9 +84,39 @@ def ner(text):
     output = ner_pipeline(text)
     return {"text": text, "entities": output}
 
-demo = gr.Interface(ner,
+css = '''
+h1{margin-bottom: 0 !important}
+'''
+
+with gr.Blocks(css=css) as demo:
+    gr.Interface(ner,
              gr.Textbox(placeholder="Enter text here..."), 
              gr.HighlightedText(),
              examples=examples)
+    gr.Markdown("""
+# Extract Legal Entities from Insurance Documents using BERT transfomers
+
+This space use fine tuned BERT transfomers for NER of legal entities in Life Insurance demand letters.
+
+Dataset is publicly available here
+https://github.com/aws-samples/aws-legal-entity-extraction.git
+
+The model extracts the following entities:
+
+* Law Firm
+* Law Office Address
+* Insurance Company
+* Insurance Company Address
+* Policy Holder Name
+* Beneficiary Name
+* Policy Number
+* Payout
+* Required Action
+* Sender
 
+Dataset consists of legal requisition/demand letters for Life Insurance, however this approach can be used across any industry & document which may benefit from spatial data in NER training.
+## Finetuning BERT Transformers model
+```source/services/ner/train/train.py```
+This code fine tune the BERT model and uploads to huggingface
+""")
 demo.launch(server_name=settings.SERVER_HOST, server_port=settings.PORT)