import os
from ct2_transformers import TransformerConverter

# 1. Define the source Hugging Face model
model_name = "Helsinki-NLP/opus-mt-tc-big-en-ar"

# 2. Define the output path for the converted model
output_dir = "en_ar_ct2_model"

# Create the output directory if it doesn't exist
if not os.path.exists(output_dir):
    os.makedirs(output_dir)

print(f"Starting conversion of model: {model_name}")
print("This may take a few moments...")

# 3. Initialize the converter
converter = TransformerConverter(model_name)

# 4. Run the conversion and apply quantization for speed
converter.convert(output_dir, quantization="int8")

print(f"\nModel successfully converted and saved to the '{output_dir}' folder.")
print("You are now ready to upload this folder to your Hugging Face Space.")