Update app.py

app.py

@@ -142,7 +142,7 @@ def bi_encode(bi_enc,passages):
             
             corpus_embeddings = bi_encoder.encode(['passage: ' + sentence for sentence in passages], convert_to_tensor=True)
 
-        elif bi_enc == 'BAAI/bge-base-en':
+        elif bi_enc == 'BAAI/bge-base-en-v1.5':
 
             instruction = "Represent this sentence for searching relevant passages: "
             
@@ -191,7 +191,7 @@ def bm25_api(passages):
     
     return bm25
 
-bi_enc_options = ["BAAI/bge-base-en","multi-qa-mpnet-base-dot-v1","all-mpnet-base-v2","multi-qa-MiniLM-L6-cos-v1",'intfloat/e5-base-v2']
+bi_enc_options = ["BAAI/bge-base-en-v1.5","multi-qa-mpnet-base-dot-v1","all-mpnet-base-v2","multi-qa-MiniLM-L6-cos-v1",'intfloat/e5-base-v2']
 
 def display_df_as_table(model,top_k,score='score'):
     # Display the df with text and scores as a table
@@ -287,7 +287,7 @@ st.markdown("""There models available to choose from:""")
 st.markdown(
     """
 Model Source: 
-- Bi-Encoders - [BAAI/bge-base-en](https://huggingface.co/BAAI/bge-base-en), [multi-qa-mpnet-base-dot-v1](https://huggingface.co/sentence-transformers/multi-qa-mpnet-base-dot-v1), [all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2), [intfloat/e5-base-v2](https://huggingface.co/intfloat/e5-base-v2) and [all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2)
+- Bi-Encoders - [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5), [multi-qa-mpnet-base-dot-v1](https://huggingface.co/sentence-transformers/multi-qa-mpnet-base-dot-v1), [all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2), [intfloat/e5-base-v2](https://huggingface.co/intfloat/e5-base-v2) and [all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2)
 - Cross-Encoder - [cross-encoder/ms-marco-MiniLM-L-12-v2](https://huggingface.co/cross-encoder/ms-marco-MiniLM-L-12-v2)""")
     
 st.markdown(