Update app.py

app.py

@@ -7,6 +7,7 @@ def convert_df_to_csv(df):
     return df.to_csv().encode('utf-8')
 
 st.title('Merge Dataframes using LinkTransformer')
+st.write('LinkTransformer supports several AI-powered data wrangling operations - here is an example that allows you to use LLMs to merge data.')
 
 # Function to load DataFrame
 def load_dataframe(upload):
@@ -38,7 +39,8 @@ if df2 is not None:
 
 
 # Model selection
-model_path = st.text_input("Model path (HuggingFace or local)", value="all-MiniLM-L6-v2")
+model_path = st.text_input("Model path (HuggingFace)", value="all-MiniLM-L6-v2")
+st_write("We have trained several record linkage models! Just copy the Hugging Face model path from the [model zoo](https://linktransformer.github.io/).")
 ##More on model selection available on https://linktransformer.github.io/
 
 if df1_upload is not None and df2_upload is not None:
@@ -71,5 +73,6 @@ else:
     st.write("Please upload or enter paths for both DataFrames.")
             
 ##Add website and citation
+st.write("Note that this space only supports CPU usage and is only recommended on small datasets. If you have access to the GPU, check out our python [package](https://github.com/dell-research-harvard/linktransformer/)!")
 st.write("For more information and advanced usage, please visit the [LinkTransformer website](https://linktransformer.github.io/).")
 st.write("If you use LinkTransformer in your research, please cite the following paper: [LinkTransformer: A Unified Package for Record Linkage with Transformer Language Models](https://arxiv.org/abs/2309.00789)")