fix: docker arg step

cloudbuild.yaml

@@ -6,7 +6,7 @@ steps:
     args: 
       - -c
       - | 
-          docker build -t us-central1-docker.pkg.dev/${PROJECT_ID}/interview-ai-detector/model-prediction:latest --build-arg=HF_TOKEN=$$_HF_TOKEN .
+          docker build -t us-central1-docker.pkg.dev/${PROJECT_ID}/interview-ai-detector/model-prediction:latest --build-arg HF_TOKEN=$$_HF_TOKEN .
 
   - name: "gcr.io/cloud-builders/docker"
     args:
@@ -15,6 +15,10 @@ steps:
         "us-central1-docker.pkg.dev/${PROJECT_ID}/interview-ai-detector/model-prediction:latest",
       ]
 
+options:
+  pool:
+    name: 'projects/${PROJECT_ID}/locations/us-central1/workerPools/ai-detector-builder'
+
 images:
   - "us-central1-docker.pkg.dev/${PROJECT_ID}/interview-ai-detector/model-prediction:latest"
 

core-model-prediction/Dockerfile

@@ -1,6 +1,3 @@
-# HF Token args
-ARG HF_TOKEN
-
 # Use an official Python runtime as a base image
 FROM pytorch/pytorch:2.1.2-cuda12.1-cudnn8-runtime
 
@@ -20,8 +17,8 @@ RUN python -m nltk.downloader punkt wordnet averaged_perceptron_tagger
 # Unzip wordnet
 RUN unzip /root/nltk_data/corpora/wordnet.zip -d /root/nltk_data/corpora/
 
-# Print masked HF Token for debugging
-RUN echo $HF_TOKEN
+# HF Token args
+ARG HF_TOKEN
 
 # Download HuggingFace model
 RUN python -c "from transformers import AutoTokenizer, AutoModelForCausalLM; \