diff --git a/.gitignore b/.gitignore
index 9c5659c..0beb08a 100644
--- a/.gitignore
+++ b/.gitignore
@@ -165,4 +165,5 @@ cython_debug/
 .vscode/**/launch.json
 
 # Data
-output/
\ No newline at end of file
+output/
+sagemaker_*.json
diff --git a/Makefile b/Makefile
index a619a24..82b091e 100644
--- a/Makefile
+++ b/Makefile
@@ -11,11 +11,11 @@ help:
 
 create-sagemaker-role:
 	@echo "Creating the SageMaker role..."
-	poetry run python llm_engineering/core/aws/create_sagemaker_role.py
+	poetry run python llm_engineering/core/aws/roles/create_sagemaker_role.py
 
 create-sagemaker-execution-role:
 	@echo "Creating the SageMaker execution role..."
-	poetry run python llm_engineering/core/aws/create_sagemaker_execution_role.py
+	poetry run python llm_engineering/core/aws/roles/create_execution_role.py
 
 deploy-inference-endpoint:
 	@echo "Deploying the inference endpoint..."
@@ -27,4 +27,7 @@ delete-inference-endpoint:
 		exit 1; \
 	fi
 	@echo "Deleting the inference endpoint and config..."
-	poetry run python llm_engineering/model/delete_inference_endpoint.py $(ENDPOINT_NAME)
\ No newline at end of file
+	poetry run python llm_engineering/model/delete_inference_endpoint.py $(ENDPOINT_NAME)
+
+test-inference:
+	poetry run python -m llm_engineering.model.inference.test
\ No newline at end of file
diff --git a/llm_engineering/core/aws/roles/create_sagemaker_role.py b/llm_engineering/core/aws/roles/create_sagemaker_role.py
index 964e280..7a4d9a1 100644
--- a/llm_engineering/core/aws/roles/create_sagemaker_role.py
+++ b/llm_engineering/core/aws/roles/create_sagemaker_role.py
@@ -1,6 +1,8 @@
 import json
+from pathlib import Path
 
 import boto3
+from loguru import logger
 
 from llm_engineering.settings import settings
 
@@ -33,19 +35,16 @@ def create_sagemaker_user(username, region_name="eu-central-1"):
     response = iam.create_access_key(UserName=username)
     access_key = response["AccessKey"]
 
-    print(f"User '{username}' created successfully.")
-    print(f"Access Key ID: {access_key['AccessKeyId']}")
-    print(f"Secret Access Key: {access_key['SecretAccessKey']}")
+    logger.info(f"User '{username}' successfully created.")
+    logger.info("Access Key ID and Secret Access Key successfully created.")
 
-    # Return the access key info
     return {"AccessKeyId": access_key["AccessKeyId"], "SecretAccessKey": access_key["SecretAccessKey"]}
 
 
 if __name__ == "__main__":
-    new_user = create_sagemaker_user("sagemaker-deployer-2")
+    new_user = create_sagemaker_user("sagemaker-deployer-3")
 
-    # Save the access keys to a file
-    with open("sagemaker_user_credentials.json", "w") as f:
+    with Path("sagemaker_user_credentials.json").open("w") as f:
         json.dump(new_user, f)
 
-print("Credentials saved to 'sagemaker_user_credentials.json'")
+logger.info("Credentials saved to 'sagemaker_user_credentials.json'")
diff --git a/llm_engineering/model/deploy/huggingface/config.py b/llm_engineering/model/deploy/huggingface/config.py
index 36ec1e0..290e1ac 100644
--- a/llm_engineering/model/deploy/huggingface/config.py
+++ b/llm_engineering/model/deploy/huggingface/config.py
@@ -1,8 +1,6 @@
 import json
 
-from sagemaker.compute_resource_requirements.resource_requirements import (
-    ResourceRequirements,
-)
+from sagemaker.compute_resource_requirements.resource_requirements import ResourceRequirements
 
 from llm_engineering.settings import settings
 
@@ -13,7 +11,7 @@
     "MAX_TOTAL_TOKENS": json.dumps(settings.MAX_TOTAL_TOKENS),  # Max length of the generation (including input text)
     "MAX_BATCH_TOTAL_TOKENS": json.dumps(settings.MAX_BATCH_TOTAL_TOKENS),
     "HUGGING_FACE_HUB_TOKEN": settings.HUGGING_FACE_HUB_TOKEN,
-    "MAX_BATCH_PREFILL_TOKENS": "25000",
+    "MAX_BATCH_PREFILL_TOKENS": "10000",
     # 'HF_MODEL_QUANTIZE': "bitsandbytes",
 }
 
diff --git a/llm_engineering/model/inference/run.py b/llm_engineering/model/inference/run.py
index 327e69b..0add42c 100644
--- a/llm_engineering/model/inference/run.py
+++ b/llm_engineering/model/inference/run.py
@@ -26,6 +26,7 @@ def execute(self) -> str:
             },
         )
         extraction = self.llm.inference()[0]["generated_text"]
+
         return extraction
 
 
diff --git a/llm_engineering/model/inference/test.py b/llm_engineering/model/inference/test.py
index 13f3a1d..7f09a25 100644
--- a/llm_engineering/model/inference/test.py
+++ b/llm_engineering/model/inference/test.py
@@ -1,3 +1,5 @@
+from loguru import logger
+
 from llm_engineering.model.inference.inference import LLMInferenceSagemakerEndpoint
 from llm_engineering.model.inference.run import InferenceExecutor
 from llm_engineering.settings import settings
@@ -8,4 +10,6 @@
     llm = LLMInferenceSagemakerEndpoint(
         endpoint_name=settings.SAGEMAKER_ENDPOINT_INFERENCE, inference_component_name=None
     )
-    InferenceExecutor(llm, text, prompt).execute()
+    answer = InferenceExecutor(llm, text, prompt).execute()
+
+    logger.info(answer)
diff --git a/llm_engineering/settings.py b/llm_engineering/settings.py
index 9f319cb..0525011 100644
--- a/llm_engineering/settings.py
+++ b/llm_engineering/settings.py
@@ -12,7 +12,7 @@ class Config:
 
     # Selenium Drivers
     SELENIUM_BROWSER_BINARY_PATH: str | None = None
-    SELENIUM_BROWSER_DRIVER_PATH: str
+    SELENIUM_BROWSER_DRIVER_PATH: str | None = None
 
     # LinkedIn Credentials
     LINKEDIN_USERNAME: str | None = None
@@ -42,14 +42,14 @@ class Config:
     COMET_WORKSPACE: str | None = None
     COMET_PROJECT: str | None = None
 
-    ARN_ROLE: str
+    ARN_ROLE: str | None = None
     HUGGING_FACE_HUB_TOKEN: str
 
-    HF_MODEL_ID: str = "test"
-    GPU_INSTANCE_TYPE: str = "test"
+    HF_MODEL_ID: str = "crumb/nano-mistral"
+    GPU_INSTANCE_TYPE: str = "ml.g5.xlarge"
     SM_NUM_GPUS: int = 1
-    MAX_INPUT_LENGTH: int = 20000
-    MAX_TOTAL_TOKENS: int = 32000
+    MAX_INPUT_LENGTH: int = 8000
+    MAX_TOTAL_TOKENS: int = 12000
     MAX_BATCH_TOTAL_TOKENS: int = 12000
     COPIES: int = 4  # Number of replicas
     GPUS: int = 1  # Number of GPUs