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Download scripts/train_bambara.py from MataStrategy/ground-zero: direct link, hf CLI and curl.
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- Download file 708 Bytes
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https://huggingface.co/spaces/MataStrategy/ground-zero/resolve/da3a060a94f7069c09b0018b49146a7cd2276d61/scripts/train_bambara.py
- Command line
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hf download hf://spaces/MataStrategy/ground-zero@da3a060a94f7069c09b0018b49146a7cd2276d61/scripts/train_bambara.py
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curl -L -o train_bambara.py https://huggingface.co/spaces/MataStrategy/ground-zero/resolve/da3a060a94f7069c09b0018b49146a7cd2276d61/scripts/train_bambara.py
708 Bytes
| """ | |
| Phase 3a: Fine-tune LoRA adapter for Bambara (bam). | |
| Usage: | |
| python scripts/train_bambara.py | |
| """ | |
| import logging | |
| import sys | |
| from pathlib import Path | |
| sys.path.insert(0, str(Path(__file__).parent.parent)) | |
| from dotenv import load_dotenv | |
| load_dotenv() | |
| logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s %(name)s — %(message)s") | |
| from src.training.trainer import WhisperLoRATrainer | |
| if __name__ == "__main__": | |
| trainer = WhisperLoRATrainer( | |
| base_config_path="configs/base_config.yaml", | |
| language_config_path="configs/lora_bambara.yaml", | |
| ) | |
| trainer.setup() | |
| trainer.train() | |
| print("\nBambara training complete. Adapter saved to adapters/bambara/") | |