Update link in README

README.md

@@ -80,7 +80,7 @@ from sagemaker.jumpstart.model import JumpStartModel
 
 model = JumpStartModel(
     model_id="autogluon-forecasting-chronos-bolt-base",
-    instance_type="ml.m5.2xlarge",
+    instance_type="ml.c5.2xlarge",
 )
 predictor = model.deploy()
 ```
@@ -99,7 +99,7 @@ payload = {
 }
 forecast = predictor.predict(payload)["predictions"]
 ```
-Chronos-Bolt models can be deployed to both CPU and GPU instances. These models also support **forecasting with covariates**. For more details about the endpoint API, check out the [example notebook](https://github.com/aws/amazon-sagemaker-examples/blob/default/%20%20%20%20generative_ai/sm-jumpstart_time_series_forecasting.ipynb).
+Chronos-Bolt models can be deployed to both CPU and GPU instances. These models also support **forecasting with covariates**. For more details about the endpoint API, check out the [example notebook](https://github.com/amazon-science/chronos-forecasting/blob/main/notebooks/deploy-chronos-bolt-to-amazon-sagemaker.ipynb).
 
 ## Citation