digiphyte/fluister-base

Fluister (base)

Fluister is an Afrikaans-optimised Whisper. ("Fluister" is Afrikaans for "to whisper".) It is a fine-tune of OpenAI Whisper (openai/whisper-base), merged into the base weights and converted to CTranslate2 (int8) for use with faster-whisper. By DigiPhyte (Pty) Ltd, South Africa.

On Afrikaans audio it reduces Whisper's drift to Dutch-style spellings ("gebou" not "gebouw", "mense" not "mensen") compared to stock Whisper whisper-base. As one of the smallest Whisper sizes its overall accuracy is limited; please read Limitations below before using it.

Use (faster-whisper)

from faster_whisper import WhisperModel
model = WhisperModel("digiphyte/fluister-base", device="cuda", compute_type="int8_float16")  # CPU: device="cpu", compute_type="int8"
segments, info = model.transcribe("audio.wav", language="af", beam_size=5)
for s in segments:
    print(s.text)

Pass language="af"; the Fluister models are tuned for Afrikaans and SA English and should be told the language rather than relying on auto-detect.

Limitations

Fluister narrows one specific failure: Whisper spelling Afrikaans as Dutch. It does not turn a small model into a large one. Absolute accuracy is still bounded by the base size, language auto-detect can still mislabel the audio (tell it language="af"), and proper nouns, numbers, and rare or technical terms can still be wrong. For English-only audio, stock Whisper or a larger size is usually the better choice.

This is the smallest, fastest tier (base), meant for very modest or CPU-only machines. It cuts the Dutch drift relative to stock Whisper whisper-base, but it is the least accurate model in the Fluister family: expect noticeably more errors overall, weaker Afrikaans/English code-switching (some Afrikaans words can leak into English passages), and weaker proper nouns. It is a speed-and-size trade-off, not a quality model. If your machine can run them, prefer fluister-medium or fluister-large-v3.

Licence and attribution

MIT (see LICENSE). This is a derivative work; the base model (OpenAI Whisper, Apache-2.0) and the training data (andreoosthuizen/afrikaans-30s, CC-BY-4.0) (this size was fine-tuned by DigiPhyte directly on that dataset) are credited in NOTICE.