Update app.py

app.py

@@ -10,7 +10,7 @@ q_encoder = SentenceTransformer(modules=[
     models.Pooling(word_embedding_dimension=768, pooling_mode='cls'),
 ])
 doc_embeddings = torch.load('checkpoints/doc_embeddings.pt', map_location=torch.device('cpu'))
-docs = pd.DataFrame(load_dataset("antoiloui/bsard", data_files="articles_fr.csv")['train'])
+docs = pd.DataFrame(load_dataset("maastrichtlawtech/bsard", data_files="articles_fr.csv")['train'])
 
 def search(question):
     q_emb = q_encoder.encode(question, convert_to_tensor=True)