update

README.md

@@ -21,7 +21,7 @@ ko-reranker는 [BAAI/bge-reranker-larger](https://huggingface.co/BAAI/bge-rerank
 
 ## 1.Usage
 
-- Local
+- using Transformers
 ```
     def exp_normalize(x):
       b = x.max()
@@ -44,6 +44,62 @@ ko-reranker는 [BAAI/bge-reranker-larger](https://huggingface.co/BAAI/bge-rerank
         print (f'first: {scores[0]}, second: {scores[1]}')
 ```
 
+- using SageMaker
+```
+import sagemaker
+import boto3
+from sagemaker.huggingface import HuggingFaceModel
+
+try:
+	role = sagemaker.get_execution_role()
+except ValueError:
+	iam = boto3.client('iam')
+	role = iam.get_role(RoleName='sagemaker_execution_role')['Role']['Arn']
+
+# Hub Model configuration. https://huggingface.co/models
+hub = {
+	'HF_MODEL_ID':'Dongjin-kr/ko-reranker',
+	'HF_TASK':'text-classification'
+}
+
+# create Hugging Face Model Class
+huggingface_model = HuggingFaceModel(
+	transformers_version='4.28.1',
+	pytorch_version='2.0.0',
+	py_version='py310',
+	env=hub,
+	role=role, 
+)
+
+# deploy model to SageMaker Inference
+predictor = huggingface_model.deploy(
+	initial_instance_count=1, # number of instances
+	instance_type='ml.g5.large' # ec2 instance type
+)
+
+runtime_client = boto3.Session().client('sagemaker-runtime')
+payload = json.dumps(
+    {
+        "inputs": [
+            {"text": "나는 너를 싫어해", "text_pair": "나는 너를 사랑해"},
+            {"text": "나는 너를 좋아해", "text_pair": "너에 대한 나의 감정은 사랑 일 수도 있어"}
+        ]
+    }
+)
+
+response = runtime_client.invoke_endpoint(
+    EndpointName="<endpoint-name>",
+    ContentType="application/json",
+    Accept=application/json",
+    Body=payload
+)
+
+## deserialization
+out = json.loads(response['Body'].read().decode()) ## for json
+print (f'Response: {out}')
+
+```
+
 ## 2. Backgound
 - #### <span style="#FF69B4;"> **컨택스트 순서가 정확도에 영향 준다**([Lost in Middel, *Liu et al., 2023*](https://arxiv.org/pdf/2307.03172.pdf)) </span>