download_model.py

#!/usr/bin/env python3
"""
Download script for DeepCoder model
Downloads and caches the model for faster container startup
"""

import os
import logging
from transformers import AutoTokenizer, AutoModelForCausalLM
from huggingface_hub import snapshot_download

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

MODEL_NAME = os.getenv("MODEL_NAME", "ai/deepcoder-preview")
CACHE_DIR = os.getenv("HUGGINGFACE_HUB_CACHE", "/app/cache")

def download_model():
    """Download the model and tokenizer"""
    try:
        logger.info(f"Downloading model: {MODEL_NAME}")
        
        # Download model files
        snapshot_download(
            repo_id=MODEL_NAME,
            cache_dir=CACHE_DIR,
            resume_download=True
        )
        
        # Verify by loading tokenizer
        tokenizer = AutoTokenizer.from_pretrained(
            MODEL_NAME,
            cache_dir=CACHE_DIR,
            trust_remote_code=True
        )
        
        logger.info("Model downloaded successfully")
        logger.info(f"Vocab size: {tokenizer.vocab_size}")
        logger.info(f"Cache directory: {CACHE_DIR}")
        
        return True
        
    except Exception as e:
        logger.error(f"Error downloading model: {str(e)}")
        return False

if __name__ == "__main__":
    success = download_model()
    if not success:
        exit(1)
    logger.info("Download complete!")