Update vector_store.py

vector_store.py

@@ -44,7 +44,7 @@ def apply_corrections(text):
 
 # --------------------------------
 # Load the embedding model
-def get_embeddings(model_name="intfloat/multilingual-e5-large-instruct", device="cuda"):
+def get_embeddings(model_name="sentence-transformers/all-MiniLM-L6-v2", device="cuda"):
     return HuggingFaceEmbeddings(
         model_name=model_name,
         model_kwargs={'device': device},
@@ -111,7 +111,7 @@ if __name__ == "__main__":
     parser.add_argument("--folder", type=str, default="dataset", help="Path to the folder containing the documents")
     parser.add_argument("--save_path", type=str, default="vector_db", help="Path to save the vector store")
     parser.add_argument("--batch_size", type=int, default=16, help="Batch size")
-    parser.add_argument("--model_name", type=str, default="intfloat/multilingual-e5-large-instruct", help="Name of the embedding model")
+    parser.add_argument("--model_name", type=str, default="sentence-transformers/all-MiniLM-L6-v2", help="Name of the embedding model")
     parser.add_argument("--device", type=str, default="cuda", choices=["cuda", "cpu"], help="Device to use ('cuda' or 'cpu')")
 
     args = parser.parse_args()