Bolo Tiny: a 0.8 MB Hinglish command model

Bolo Tiny is the command-understanding model in 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

Loading uses the bolo package (bolo.models.tiny) from the GitHub repo, because the PhonoHash featuriser is part of it:

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

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 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. Every seed and ablation checkpoint is on the GitHub release.

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.