Update context_relevancy_lora/README.md

context_relevancy_lora/README.md

@@ -60,7 +60,8 @@ To prompt the LoRA adapter to determine context relevancy, a special context rel
 
 ## Quickstart Example
 
-Use the code below to get started with the model.
+Use the code below to get started with the model. Before running the script, set the `LORA_NAME` parameter to the path of the directory that you downloaded the LoRA adapter. The download process is explained [here](https://huggingface.co/ibm-granite/granite-3.3-8b-rag-agent-lib#quickstart-example). 
+
 ```python
 import  torch
 from  transformers  import  AutoTokenizer,  AutoModelForCausalLM
@@ -71,7 +72,7 @@ device=torch.device('cuda' if torch.cuda.is_available() else 'cpu')
 
 CONTEXT_RELEVANCY_PROMPT = "<|start_of_role|>context_relevance<|end_of_role|>"
 BASE_NAME = "ibm-granite/granite-3.3-8b-instruct"
-LORA_NAME = "ibm-granite/granite-3.3-8b-lora-rag-context-relevance-prediction"
+LORA_NAME = "PATH_TO_DOWNLOADED_DIRECTORY"
 
 tokenizer = AutoTokenizer.from_pretrained(BASE_NAME, padding_side='left',trust_remote_code=True)
 model_base = AutoModelForCausalLM.from_pretrained(BASE_NAME,device_map="auto")