diff --git a/docs/tutorials/semantic_search/asymmetric_embedding_model.md b/docs/tutorials/semantic_search/asymmetric_embedding_model.md
new file mode 100644
index 0000000000..49b46c446e
--- /dev/null
+++ b/docs/tutorials/semantic_search/asymmetric_embedding_model.md
@@ -0,0 +1,33 @@
+# Topic
+
+This tutorial shows how to generate embeddings using a local asymmetric embedding model in OpenSearch implemented in a Docker container .
+
+Note: Replace the placeholders that start with `your_` with your own values.
+
+# Steps
+## 1. Spin up a docker OpenSearch Cluster
+
+  ###  a. Use a docker compose file
+
+## 2. Prepare the model for OpenSearch
+
+  ###  a. Clone the model
+  ###  b. Zip the contents
+  ###  c. Calculate hash
+  ###  d. service the zip file using a python server
+ 
+   -  can cancel the server now
+
+## 3. Register a model group
+## 4. Register the model
+## 5. Deploy The model
+## 6. Run Inference
+## Next steps
+
+- Create an ingest pipeline for your documents with assymetric embeddings
+- Run a query using KNN with your asymmetric model
+
+
+# References
+
+Wang, Liang, et al. (2024). *Multilingual E5 Text Embeddings: A Technical Report*. arXiv preprint arXiv:2402.05672. [Link](https://arxiv.org/abs/2402.05672)