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#!/bin/bash
# Cloud Model Recovery and Deployment Script
# Run this on your cloud instance to recover and deploy your trained model
set -e # Exit on any error
echo "🚀 Starting cloud model recovery and deployment..."
# Configuration
MODEL_PATH="/output-checkpoint"
REPO_NAME="your-username/smollm3-finetuned" # Change this to your HF username and desired repo name
HF_TOKEN="${HF_TOKEN}" # Set this environment variable
PRIVATE=false # Set to true if you want a private repository
# Colors for output
RED='\033[0;31m'
GREEN='\033[0;32m'
YELLOW='\033[1;33m'
BLUE='\033[0;34m'
NC='\033[0m' # No Color
# Function to print colored output
print_status() {
echo -e "${BLUE}[INFO]${NC} $1"
}
print_success() {
echo -e "${GREEN}[SUCCESS]${NC} $1"
}
print_warning() {
echo -e "${YELLOW}[WARNING]${NC} $1"
}
print_error() {
echo -e "${RED}[ERROR]${NC} $1"
}
# Check if we're in the right directory
if [ ! -d "$MODEL_PATH" ]; then
print_error "Model path not found: $MODEL_PATH"
exit 1
fi
print_status "Found model at: $MODEL_PATH"
# Check for required files
print_status "Validating model files..."
if [ ! -f "$MODEL_PATH/config.json" ]; then
print_error "config.json not found"
exit 1
fi
if [ ! -f "$MODEL_PATH/model.safetensors.index.json" ]; then
print_error "model.safetensors.index.json not found"
exit 1
fi
if [ ! -f "$MODEL_PATH/tokenizer.json" ]; then
print_error "tokenizer.json not found"
exit 1
fi
print_success "Model files validated"
# Check HF token
if [ -z "$HF_TOKEN" ]; then
print_error "HF_TOKEN environment variable not set"
print_status "Please set your Hugging Face token:"
print_status "export HF_TOKEN=your_token_here"
exit 1
fi
print_success "HF Token found"
# Install required packages if not already installed
print_status "Checking dependencies..."
python3 -c "import torchao" 2>/dev/null || {
print_status "Installing torchao..."
pip install torchao
}
python3 -c "import huggingface_hub" 2>/dev/null || {
print_status "Installing huggingface_hub..."
pip install huggingface_hub
}
print_success "Dependencies checked"
# Run the recovery script
print_status "Running model recovery and deployment pipeline..."
python3 recover_model.py \
"$MODEL_PATH" \
"$REPO_NAME" \
--hf-token "$HF_TOKEN" \
--private "$PRIVATE" \
--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 [ $? -eq 0 ]; then
print_success "Model recovery and deployment completed successfully!"
print_success "View your model at: https://huggingface.co/$REPO_NAME"
print_success "Quantized models available at:"
print_success " - https://huggingface.co/$REPO_NAME/int8 (GPU optimized)"
print_success " - https://huggingface.co/$REPO_NAME/int4 (CPU optimized)"
else
print_error "Model recovery and deployment failed!"
exit 1
fi
print_success "🎉 All done! Your model has been successfully recovered and deployed to Hugging Face Hub." |