| --- |
| license: apache-2.0 |
| language: |
| - hi |
| - en |
| pipeline_tag: token-classification |
| library_name: pytorch |
| tags: |
| - hinglish |
| - code-switching |
| - intent-classification |
| - slot-filling |
| - spoken-language-understanding |
| - on-device |
| - onnx |
| --- |
| |
| # Bolo Tiny: a 0.8 MB Hinglish command model |
|
|
| Bolo Tiny is the command-understanding model in [Bolo](https://github.com/Optimus2007/bolo), an offline Hinglish |
| voice-command assistant. It reads a command in Roman, Devanagari or mixed script and returns the intent plus slots |
| (folder, app, contact, level, and so on). There are 20 command types plus "none". |
|
|
| ``` |
| "bhai rust learning folder mein terminal kholo" -> {intent: open_terminal, folder: "rust learning"} |
| ``` |
|
|
| - **Built from scratch:** 0.69M parameters. A 2-layer transformer over *PhonoHash* features: hashed character n-grams |
| of the text, its transliteration, a phonetic key and a consonant skeleton. Spelling variants like *kholo / khol do / |
| खोलो* therefore land close together. |
| - **Size and speed:** 0.8 MB as int8 ONNX, about 1 ms on one CPU thread. |
|
|
| ## Files |
|
|
| | File | What it is | |
| |---|---| |
| | `model.safetensors` (also `model.pt`, a plain state dict) + `config.json` + `threshold.json` | `phono_views_aug_asr-s0`, the default in Bolo. Trained on synthetic template text plus transcripts of TTS clips made by the speech model, so it has seen realistic speech-recognition errors | |
| | `onnx/bolo_tiny.int8.onnx`, `onnx/bolo_tiny.onnx` | ONNX export of the earlier text-only model `phono_views_aug-s0` (88.3% exact match, same as PyTorch) | |
|
|
| Loading uses the `bolo` package (`bolo.models.tiny`) from the GitHub repo, because the PhonoHash featuriser is part of |
| it: |
|
|
| ```python |
| from bolo.pipeline import Bolo |
| bolo = Bolo.load(nlu_path="path/to/this/folder") |
| bolo.understand("volume 40 pe kar do") # {'intent': 'set_volume', 'slots': {'level': 40}, ...} |
| ``` |
|
|
| ## Results |
|
|
| | | Synthetic test exact match | False actions | Size | Latency | |
| |---|---|---|---|---| |
| | Hand-written rules | 84.9 | 18.7% | – | 0.01 ms | |
| | **Bolo Tiny** (3 seeds) | **87.4** | **5.2%** | **0.8 MB** | about 1 ms | |
| | MuRIL-base fine-tuned | 91.6 | 3.6% | 950 MB | 15.6 ms | |
|
|
| With grounding (checking that the folder or app exists on the machine), Bolo Tiny gets 95.8% vs MuRIL's 96.4%, at |
| about 1/1000 of the size. Real-speech results are on the [Bolo Sun](https://huggingface.co/kungfupanda12/bolo-sun) card; |
| they come from one speaker so far. |
|
|
| **Ablations, including what failed:** |
| - PhonoHash: +5.0 |
| - data augmentation: +6.4 |
| - multi-script views: +2.5 |
| - a cross-script consistency loss: **−1.4** |
| - distillation from MuRIL: **−4.0** |
|
|
| Full details are in [WHAT_WE_TRIED.md](https://github.com/Optimus2007/bolo/blob/main/docs/WHAT_WE_TRIED.md). Every seed |
| and ablation checkpoint is on the [GitHub release](https://github.com/Optimus2007/bolo/releases/tag/weights-v1). |
|
|
| **Known weaknesses:** |
| - Confident mistakes on near-miss phrasings ("naya folder banao"). |
| - "kuch bhi random baat" is read as calling a contact named "random". |
| - All training text is synthetic. |
|
|
| ## License |
|
|
| Apache-2.0. Training text came from our own templates; no LLM-generated data is included in this model. |
|
|
