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#!/usr/bin/env python3
"""
Cloud Model Deployment Script
Run this directly on your cloud instance to deploy your trained model
"""
import os
import sys
import logging
from pathlib import Path
# Setup logging
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(levelname)s - %(message)s'
)
logger = logging.getLogger(__name__)
def main():
"""Main deployment function"""
# Configuration - CHANGE THESE VALUES
MODEL_PATH = "/output-checkpoint"
REPO_NAME = "your-username/smollm3-finetuned" # Change to your HF username and desired repo name
HF_TOKEN = os.getenv('HF_TOKEN')
PRIVATE = False # Set to True for private repository
# Validate configuration
if not HF_TOKEN:
logger.error("❌ HF_TOKEN environment variable not set")
logger.info("Please set your Hugging Face token:")
logger.info("export HF_TOKEN=your_token_here")
return 1
if not Path(MODEL_PATH).exists():
logger.error(f"❌ Model path not found: {MODEL_PATH}")
return 1
# Check for required files
required_files = ['config.json', 'model.safetensors.index.json', 'tokenizer.json']
for file in required_files:
if not (Path(MODEL_PATH) / file).exists():
logger.error(f"❌ Required file not found: {file}")
return 1
logger.info("✅ Model files validated")
# Install dependencies if needed
try:
import torchao
logger.info("✅ torchao available")
except ImportError:
logger.info("📦 Installing torchao...")
os.system("pip install torchao")
try:
import huggingface_hub
logger.info("✅ huggingface_hub available")
except ImportError:
logger.info("📦 Installing huggingface_hub...")
os.system("pip install huggingface_hub")
# Run the recovery script
logger.info("🚀 Starting model deployment...")
cmd = [
sys.executable, "recover_model.py",
MODEL_PATH,
REPO_NAME,
"--hf-token", HF_TOKEN,
"--quant-types", "int8_weight_only", "int4_weight_only",
"--author-name", "Your Name",
"--model-description", "A fine-tuned SmolLM3 model for improved text generation and conversation capabilities"
]
if PRIVATE:
cmd.append("--private")
logger.info(f"Running: {' '.join(cmd)}")
# Run the command
result = os.system(' '.join(cmd))
if result == 0:
logger.info("✅ Model deployment completed successfully!")
logger.info(f"🌐 View your model at: https://huggingface.co/{REPO_NAME}")
logger.info("📊 Quantized models available at:")
logger.info(f" - https://huggingface.co/{REPO_NAME}/int8 (GPU optimized)")
logger.info(f" - https://huggingface.co/{REPO_NAME}/int4 (CPU optimized)")
return 0
else:
logger.error("❌ Model deployment failed!")
return 1
if __name__ == "__main__":
exit(main()) |