ukta-app/indic-whisper-ggml

Indic Whisper — ggml builds for whisper.cpp

ggml + q5_1 quantized builds of Indian-language Whisper fine-tunes, for on-device speech-to-text via whisper.cpp. Used by the Ukta in-store feedback kiosk for accurate regional-language transcription.

Files

File naming: ggml-<langCode>-small.bin — q5_1 quantized, ~181 MiB each.

Language	Code	File
Hindi	hi	ggml-hi-small.bin
Kannada	kn	ggml-kn-small.bin
Tamil	ta	ggml-ta-small.bin
Telugu	te	ggml-te-small.bin
Gujarati	gu	ggml-gu-small.bin

These are monolingual — each model transcribes only its own language. Malayalam/Marathi/Odia/Punjabi/Bengali are not yet covered (no published vasista22 small fine-tune); those languages fall back to a general model.

Provenance & attribution

• Fine-tuned source models: vasista22 (whisper-<language>-{base,small}), © Speech Lab, IIT Madras — Apache 2.0.
• Base architecture/weights: OpenAI Whisper — MIT.
• Training corpora include AI4Bharat datasets (Shrutilipi, Vistaar) and Fleurs (CC-BY).
• Conversion: whisper.cpp/models/convert-h5-to-ggml.py → f16 ggml, then quantize ... q5_1.

This repository redistributes derivatives of the above under the Apache License 2.0; see LICENSE. No change was made to the model weights other than format conversion and quantization.