add secretes

app/embedding_setup.py

@@ -33,11 +33,12 @@ retriever = db.as_retriever(search_kwargs={"k": TOP_K})
 LLM_MODEL = "meta-llama/Meta-Llama-3-8B-Instruct"
 lora_weights = "/hpcwork/vg380347/llama3/Instruct_8B_EngGer_alpaca_finetune_pairwise_skill_24_128/last_checkpoint"
 
+hf_auth  = os.environ.get("SECRET_EXAMPLE")
 
 
-tokenizer = AutoTokenizer.from_pretrained(LLM_MODEL, cache_dir="/hpcwork/vg380347/.cache")
+tokenizer = AutoTokenizer.from_pretrained(LLM_MODEL, token=hf_auth, cache_dir="/hpcwork/vg380347/.cache")
 LLM_model = AutoModelForCausalLM.from_pretrained(
-    LLM_MODEL,  device_map="auto",  trust_remote_code=True
+    LLM_MODEL, token=hf_auth, device_map="auto",  trust_remote_code=True
 )
 
 first_token = 'First'