Update app.py

app.py

@@ -11,12 +11,12 @@ from datasets import load_dataset
 
 #@st.cache
 @st.cache_data
-def read_data(dataset_repo='dhmeltzer/asks_validation_embedded'):
+def read_data(dataset_repo='dhmeltzer/ELI5_embedded'):
     """Read the data from huggingface."""
     return load_dataset(dataset_repo)['validation_asks']
 
 @st.cache_data
-def load_faiss_index(path_to_faiss="./faiss_index_small.pickle"):
+def load_faiss_index(path_to_faiss="./faiss_index.pickle"):
     """Load and deserialize the Faiss index."""
     with open(path_to_faiss, "rb") as h:
         data = pickle.load(h)
@@ -25,11 +25,9 @@ def load_faiss_index(path_to_faiss="./faiss_index_small.pickle"):
 def main():
     # Load data and models
     data = read_data()
-    #model = load_bert_model()
-    #tok = load_tokenizer()
     faiss_index = load_faiss_index()
 
-    model_id="sentence-transformers/nli-distilbert-base"
+    model_id="sentence-transformers/all-MiniLM-L6-v2"
     
     api_url = f"https://api-inference.huggingface.co/pipeline/feature-extraction/{model_id}"
     headers = {"Authorization": f"Bearer {st.secrets['HF_token']}"}
@@ -65,6 +63,7 @@ def main():
             
             
             st.write(f"**Title**: {row['title']}")
+            st.write(f"**Split**: {row['split']}")
             st.write(f"**Score**: {row['answers']['score'][0]}")
             st.write(f"**Top Answer**: {answers[0]}")
             st.write("-"*20)