Updated Dockerfile for Hugging Face Spaces deployment

Dockerfile

@@ -44,12 +44,13 @@ ENV PATH=${CUDA_HOME}/bin:${PATH}
 # Optionally set LD_LIBRARY_PATH for CUDA libraries
 ENV LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
 
-# Create cache directory with appropriate permissions
-RUN mkdir -p /app/.cache/huggingface && chmod -R 777 /app/.cache/huggingface
+# Create cache directory
+RUN mkdir -p /app/cache/huggingface
+RUN chmod -R 777 /app/cache/huggingface
 
-# Set environment variables for Hugging Face cache directory
-ENV HF_HOME=/app/.cache/huggingface
-ENV TRANSFORMERS_CACHE=/app/.cache/huggingface
+# Set environment variables for cache directory
+ENV HF_HOME=/app/cache/huggingface
+ENV TRANSFORMERS_CACHE=/app/cache/huggingface
 
 # Copy the setup script and requirements file into the container
 COPY setup.sh requirements.txt /app/

models/nllb.py

@@ -21,13 +21,8 @@ def nllb():
     # Load the tokenizer and model
     # Set Hugging Face cache directory
     # Ensure the cache directory exists and has the correct permissions
-    cache_dir = "/app/.cache/huggingface"
-    if not os.path.exists(cache_dir):
-        os.makedirs(cache_dir)
-    os.chmod(cache_dir, 0o777)
-
-    os.environ['HF_HOME'] = cache_dir
-    os.environ['TRANSFORMERS_CACHE'] = cache_dir
+    os.environ['HF_HOME'] = '/app/cache/huggingface'
+    os.environ['TRANSFORMERS_CACHE'] = '/app/cache/huggingface'
 
     # Load models
     tokenizer = AutoTokenizer.from_pretrained("facebook/nllb-200-distilled-1.3B")