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| # Notebooks | |
| Exploratory analysis and Colab training notebooks. Run them in order. The | |
| first is best run locally; the training ones expect a Colab (T4+/A100) or | |
| CUDA GPU environment. | |
| | Notebook | Purpose | | |
| |----------|---------| | |
| | `01_data_exploration.ipynb` | Dataset overview, language distribution, label stats | | |
| | `02_train_colab.ipynb` | End-to-end training (aspect extraction + sentiment) on Colab | | |
| | `03_model_comparison.ipynb` | Compare trained runs from the MLflow tracking server | | |
| | `04_qlora_colab.ipynb` | QLoRA 4-bit fine-tuning of the sequence classifier | | |
| | `05_final_evaluation.ipynb` | Final cross-lingual evaluation and latency benchmarks | | |
| These notebooks are generated/updated from `scripts/generate_notebooks.py` | |
| where applicable. |