Update pages/Workflow & Model Overview.py

pages/Workflow & Model Overview.py

@@ -63,10 +63,10 @@ st.markdown("""
 </div>
 """, unsafe_allow_html=True)
 
-st.markdown('<div class="sub-title">Installation</div>')
+st.markdown('<div class="sub-title">Installation</div>', unsafe_allow_html=True)
 st.code('!pip install spark-nlp', language='python')
 
-st.markdown('<div class="sub-title">Import Libraries and Start Spark Session</div>')
+st.markdown('<div class="sub-title">Import Libraries and Start Spark Session</div>', unsafe_allow_html=True)
 st.code("""
 import sparknlp
 from sparknlp.base import DocumentAssembler, PipelineModel
@@ -82,7 +82,7 @@ st.markdown("""
 </div>
 """, unsafe_allow_html=True)
 
-st.markdown('<div class="sub-title">Define the Pipeline</div>')
+st.markdown('<div class="sub-title">Define the Pipeline</div>', unsafe_allow_html=True)
 st.code("""
 # Transforms raw texts into `document` annotation
 document_assembler = (
@@ -106,7 +106,7 @@ st.markdown("""
 </div>
 """, unsafe_allow_html=True)
 
-st.markdown('<div class="sub-title">Create Example DataFrame</div>')
+st.markdown('<div class="sub-title">Create Example DataFrame</div>', unsafe_allow_html=True)
 st.code("""
 example = \"""
 Transfer learning, where a model is first pre-trained on a data-rich task 
@@ -129,7 +129,7 @@ models, and code.
 spark_df = spark.createDataFrame([[example]])
 """, language='python')
 
-st.markdown('<div class="sub-title">Apply the Pipeline</div>')
+st.markdown('<div class="sub-title">Apply the Pipeline</div>', unsafe_allow_html=True)
 st.code("""
 result = pipeline.transform(spark_df)
 result.select("t5.result").show(truncate=False)