Update README.md to add a description of accessing Sionic AI's Embedding API v1

README.md

@@ -2601,4 +2601,73 @@ model-index:
 language:
 - en
 library_name: transformers
----
+---
+
+# Sionic AI Embedding API v1
+
+## About Sionic AI
+
+Homepage : https://sionic.ai/
+
+Sionic AI delivers more accessible and cost-effective AI technology addressing the various needs to boost productivity and drive innovation.
+
+The Large Language Model (LLM) is not for research and experimentation. We offer solutions that leverage LLM to add value to your business. Anyone can easily train and control AI.
+
+You can try our product [here](https://www.s9m.ai) for free! 
+
+## How to get embeddings
+
+To get embeddings, you should call API endpoint to send your text. You can send either a single sentence or multiple sentences. The embeddings that correspond to the inputs will be returned.
+
+API Endpoint : https://api.sionic.ai/v1/embedding
+
+Example request:
+```shell
+curl https://api.sionic.ai/v1/embedding \
+  -H "Content-Type: application/json" \
+  -d '{
+    "inputs": ["first query", "second query", "third query"]
+  }'
+```
+
+Example response:
+```shell
+{
+    "embedding": [
+        [
+            0.1380517,
+            0.0749767,
+            -0.0600897,
+            0.6106221,
+            -0.3284067,
+            ...
+        ],
+        [
+            -0.0237823,
+            -0.103611, 
+            -0.0491666, 
+            0.671397, 
+            -0.8827474, 
+            ...
+        ],
+        [
+            0.0137392,
+            -0.1101281,
+            -0.2256125,
+            0.7899137,
+            -0.8847492,
+            ...
+        ]
+    ]
+}
+```
+
+## Massive Text Embedding Benchmark (MTEB) Evaluation
+
+Both versions of Sionic AI's embedding show the state-of-the-art performances on the MTEB!
+You can find a code to evaluate MTEB datasets using v1 embedding [here](https://huggingface.co/sionic-ai/sionic-ai-v1/blob/main/mteb_evaluate.py).
+
+|                               Model Name                                | Dimension | Sequence Length | Average (56) | 
+|:-----------------------------------------------------------------------:|:---------:|:---:|:------------:|
+| [sionic-ai/sionic-ai-v2](https://huggingface.co/sionic-ai/sionic-ai-v2) |   3072    | 512 |  **65.23**   |  
+| [sionic-ai/sionic-ai-v1](https://huggingface.co/sionic-ai/sionic-ai-v1) |   2048    | 512 |    64.92     |