Update app.py

app.py

@@ -16,7 +16,7 @@ st.markdown('''<img src="https://huggingface.co/spaces/ncats/EpiPipeline4GARD/re
 #st.markdown("![National Center for Advancing Translational Sciences (NCATS) Logo](https://huggingface.co/spaces/ncats/EpiPipeline4GARD/resolve/main/NCATS_logo.png")
 #st.markdown('''<img src="https://huggingface.co/spaces/ncats/EpiPipeline4GARD/raw/main/NCATS_logo.svg" alt="National Center for Advancing Translational Sciences Logo" width="800" height="300">''',unsafe_allow_html=True)
 st.title("Epidemiology Extraction Pipeline for Rare Diseases")
-st.subheader("National Center for Advancing Translational Sciences (NIH/NCATS)") 
+#st.subheader("National Center for Advancing Translational Sciences (NIH/NCATS)") 
 
 #### CHANGE SIDEBAR WIDTH ###
 st.markdown(
@@ -72,7 +72,8 @@ with st.spinner('Loading Epidemiology Models and Dependencies...'):
     #classify_model_vars = (nlp, nlpSci, nlpSci2, classify_model, classify_tokenizer)
 st.success('All Models and Dependencies Loaded!')
 
-disease_or_gard_id = st.text_input("Input a rare disease term or GARD ID.")
+disease_or_gard_id = st.text_input("Input a rare disease term or GARD ID such as Fellman syndrome, Classic Homocystinuria, phenylketonuria, GARD:000941")
+st.markdown("A full list of rare diseases tracked by GARD can be found [here](https://rarediseases.info.nih.gov/diseases/browse-by-first-letter)")
 
 if disease_or_gard_id:
   df = extract_abs.streamlit_extraction(disease_or_gard_id, max_results, filtering,