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| import os | |
| from huggingface_hub import snapshot_download | |
| def download_model(): | |
| """ | |
| Downloads the NLLB model from Hugging Face Hub. | |
| """ | |
| # --- Configuration --- | |
| # Note: The original script referred to 'nllb-finetuned-nepali-en', which is not a public model. | |
| # We are downloading the base model 'facebook/nllb-200-distilled-600M' instead. | |
| # You may need to fine-tune this model on your own dataset to get the desired performance. | |
| model_name = "facebook/nllb-200-distilled-600M" | |
| # --- Path setup --- | |
| # Construct the path to save the model, relative to this script's location. | |
| script_dir = os.path.dirname(os.path.abspath(__file__)) | |
| # We want to save it in saksi_translation/models/nllb-finetuned-nepali-en | |
| target_dir = os.path.abspath(os.path.join(script_dir, '..', 'models', 'nllb-finetuned-nepali-en')) | |
| print(f"Downloading model: {model_name}") | |
| print(f"Saving to: {target_dir}") | |
| # --- Download --- | |
| try: | |
| if not os.path.exists(target_dir): | |
| os.makedirs(target_dir) | |
| snapshot_download(repo_id=model_name, local_dir=target_dir, local_dir_use_symlinks=False) | |
| print("Model downloaded successfully.") | |
| except Exception as e: | |
| print(f"An error occurred during download: {e}") | |
| if __name__ == "__main__": | |
| download_model() | |