Update README.md

Fixed the model name and sparse vector format

README.md

@@ -68,7 +68,7 @@ client.create_collection(
 )
 
 embeddings_model = model.sparse.SpladeEmbeddingFunction(
-    model_name="ibm-granite/granite-embedding-30m-sparse/", 
+    model_name="ibm-granite/granite-embedding-30m-sparse", 
     device="cpu",
     batch_size=2,
     k_tokens_query=50,
@@ -81,7 +81,11 @@ docs = [
     "Alan Turing was the first person to conduct substantial research in AI.",
     "Born in Maida Vale, London, Turing was raised in southern England.",
 ]
-doc_vector = [{"embeddings": doc_emb, "id": f"item_{i}"} for i, doc_emb in enumerate(embeddings_model.encode_documents(docs))]
+
+# SpladeEmbeddingFunction.encode_documents returns sparse matrix or sparse array depending
+# on the milvus-model version. reshape(1,-1) ensures the format is correct for ingestion.
+doc_vector = [{"embeddings": doc_emb.reshape(1,-1), "id": f"item_{i}"} for i, doc_emb in enumerate(embeddings_model.encode_documents(docs))]
+
 
 client.insert(
     collection_name="my_sparse_collection",