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--- |
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language: |
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- en |
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- grt |
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tags: |
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- embeddings |
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- bilingual |
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- garo |
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- low-resource |
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license: cc-by-sa-4.0 |
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datasets: |
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- private |
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model-index: |
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- name: GaroVec v1.0 |
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results: [] |
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--- |
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# GaroVec v1.0 — Hybrid English↔Garo Embeddings |
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[](https://doi.org/10.5281/zenodo.17083589) |
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## Overview |
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**GaroVec v1.0** is the *first publicly documented Latin-script Garo embedding model*. |
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It combines: |
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- **FastText embeddings** (English + Garo) |
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- **Cross-lingual alignment** using Procrustes rotation |
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- **Frequency-based bilingual dictionary** for high-confidence word translations |
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This hybrid design provides both **semantic embeddings** and **direct dictionary lookups**, making it useful for cross-lingual tasks like translation support, lexicon building, and low-resource NLP research. |
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--- |
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## Training |
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- **Data size**: ~2,500 English ↔ Garo parallel sentences |
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(synthetic English generated with open models, manually translated by native Garo speakers) |
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- **Method**: |
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- FastText skipgram (300-dimensional vectors, char n-grams 3–6, 25 epochs) |
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- Linear alignment (Procrustes) between English and Garo vector spaces |
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- Frequency-based dictionary extracted from the parallel corpus |
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- **Artifacts**: |
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- `garovec_garo.bin` — Garo FastText embeddings |
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- `garovec_english.bin` — English FastText embeddings |
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- `garovec_alignment_matrix.npy` — alignment matrix |
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- `garovec_model.pkl` — final hybrid model with dictionary + embeddings |
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--- |
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## Usage |
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```python |
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import pickle |
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import fasttext |
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import numpy as np |
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# Load hybrid model data |
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with open("garovec_model.pkl", "rb") as f: |
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garovec_data = pickle.load(f) |
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# Load embeddings |
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garo_model = fasttext.load_model("garovec_garo.bin") |
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english_model = fasttext.load_model("garovec_english.bin") |
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W = np.load("garovec_alignment_matrix.npy") |
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# Example: get nearest Garo words for English word |
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vec = english_model.get_word_vector("love") |
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aligned_vec = vec @ W |
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candidates = [garo_model.get_word_vector(w) for w in garo_model.words[:100]] |
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``` |
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--- |
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## Limitations |
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- Trained on a **small parallel dataset** (~2.5k sentences). |
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- Optimized for **demonstrations, lexicon building, and low-resource NLP exploration**. |
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- Future versions will incorporate more data and advanced techniques for broader coverage. |
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--- |
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## License |
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- **Model weights & code**: CC-BY-SA 4.0 |
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- **Training data**: private, not released |
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--- |
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## Citation |
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If you use **GaroVec v1.0**, please cite: |
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``` |
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MWire Labs. 2025. GaroVec v1.0 — Hybrid English↔Garo Embeddings. Hugging Face. |
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``` |
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--- |
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## Acknowledgements |
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Built by **MWire Labs** with contributions from native Garo speakers. |
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This release is part of the **NEODAC project** (Northeast India Domain-Adapted Corpus). |
