diff --git a/comps/guardrails/README.md b/comps/guardrails/README.md
index 1107e7fe47..4407a4647e 100644
--- a/comps/guardrails/README.md
+++ b/comps/guardrails/README.md
@@ -38,9 +38,9 @@ export LANGCHAIN_TRACING_V2=true
 export LANGCHAIN_API_KEY=${your_langchain_api_key}
 export LANGCHAIN_PROJECT="opea/gaurdrails"
 volume=$PWD/data
-model_id="meta-llama/LlamaGuard-7b"
-docker pull ghcr.io/huggingface/tgi-gaudi:1.2.1
-docker run -p 8088:80 -v $volume:/data --runtime=habana -e HABANA_VISIBLE_DEVICES=all -e OMPI_MCA_btl_vader_single_copy_mechanism=none --cap-add=sys_nice --ipc=host -e HTTPS_PROXY=$https_proxy -e HTTP_PROXY=$https_proxy ghcr.io/huggingface/tgi-gaudi:1.2.1 --model-id $model_id
+model_id="meta-llama/Meta-Llama-Guard-2-8B"
+docker pull ghcr.io/huggingface/tgi-gaudi:2.0.1
+docker run -p 8088:80 -v $volume:/data --runtime=habana -e HABANA_VISIBLE_DEVICES=all -e OMPI_MCA_btl_vader_single_copy_mechanism=none --cap-add=sys_nice --ipc=host -e HTTPS_PROXY=$https_proxy -e HTTP_PROXY=$https_proxy ghcr.io/huggingface/tgi-gaudi:2.0.1 --model-id $model_id
 ```
 
 ## 1.3 Verify the TGI Gaudi Service
@@ -57,7 +57,7 @@ curl 127.0.0.1:8088/generate \
 Optional: If you have deployed a Guardrails model with TGI Gaudi Service other than default model (i.e., `meta-llama/LlamaGuard-7b`) [from section 1.2](## 1.2 Start TGI Gaudi Service), you will need to add the eviornment variable `SAFETY_GUARD_MODEL_ID` containing the model id. For example, the following informs the Guardrails Service the deployed model used LlamaGuard2:
 
 ```bash
-export SAFETY_GUARD_MODEL_ID="meta-llama/Meta-Llama-Guard-2-8"
+export SAFETY_GUARD_MODEL_ID="meta-llama/Meta-Llama-Guard-2-8B"
 ```
 
 ```bash
diff --git a/comps/guardrails/langchain/guardrails_tgi_gaudi.py b/comps/guardrails/langchain/guardrails_tgi_gaudi.py
index 03d1935053..34cecf5d85 100644
--- a/comps/guardrails/langchain/guardrails_tgi_gaudi.py
+++ b/comps/guardrails/langchain/guardrails_tgi_gaudi.py
@@ -90,6 +90,6 @@ def safety_guard(input: TextDoc) -> TextDoc:
         repetition_penalty=1.03,
     )
     # chat engine for server-side prompt templating
-    llm_engine_hf = ChatHuggingFace(llm=llm_guard)
+    llm_engine_hf = ChatHuggingFace(llm=llm_guard, model_id=safety_guard_model)
     print("guardrails - router] LLM initialized.")
     opea_microservices["opea_service@guardrails_tgi_gaudi"].start()