---
license: mit
language:
- af
base_model: openai/whisper-tiny
library_name: ctranslate2
pipeline_tag: automatic-speech-recognition
tags:
- whisper
- fluister
- afrikaans
- south-africa
- faster-whisper
- ctranslate2
---

# Fluister (tiny)

**Fluister** is an Afrikaans-optimised Whisper. ("Fluister" is Afrikaans for "to whisper".) It is a
fine-tune of OpenAI Whisper (openai/whisper-tiny), 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-tiny. As one of the smallest Whisper sizes its overall accuracy is limited; please read Limitations below before using it.

## Use (faster-whisper)

```python
from faster_whisper import WhisperModel
model = WhisperModel("digiphyte/fluister-tiny", 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 (tiny), meant for very modest or CPU-only machines.** It cuts the Dutch drift relative to stock Whisper whisper-tiny, 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`.