Update app.py

app.py

@@ -14,6 +14,7 @@ token = os.environ["HF_TOKEN"]
 ST = SentenceTransformer("mixedbread-ai/mxbai-embed-large-v1")
 
 dataset = load_dataset("Yoxas/statistical_literacyv2")
+data = dataset["train"]
 
 # Convert the list to a numpy array
 embeddings_array = np.array(data["Abstract_Embeddings"])
@@ -36,7 +37,7 @@ new_data.set_format("numpy", columns=["Abstract_Embeddings"])
 new_data.add_faiss_index("Abstract_Embeddings")
 
 # Now you can use the Dataset with the Faiss index
-data = dataset["train"]
+
 
 model_id = "meta-llama/Meta-Llama-3-8B-Instruct"