Aryan Mishra
Add CI, typed ORM models, and packaging cleanup
a00fee9
|
Raw
History Blame Contribute Delete
785 Bytes
# 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.