Add README.md
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README.md
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---
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license: mit
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language:
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- af
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base_model: openai/whisper-tiny
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library_name: ctranslate2
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pipeline_tag: automatic-speech-recognition
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tags:
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- whisper
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- fluister
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- afrikaans
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- south-africa
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- faster-whisper
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- ctranslate2
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---
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# Fluister (tiny)
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**Fluister** is an Afrikaans-optimised Whisper. ("Fluister" is Afrikaans for "to whisper".) It is a
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fine-tune of OpenAI Whisper (openai/whisper-tiny), merged into the base weights and converted to CTranslate2
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(int8) for use with faster-whisper. By DigiPhyte (Pty) Ltd, South Africa.
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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.
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## Use (faster-whisper)
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```python
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from faster_whisper import WhisperModel
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model = WhisperModel("digiphyte/fluister-tiny", device="cuda", compute_type="int8_float16") # CPU: device="cpu", compute_type="int8"
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segments, info = model.transcribe("audio.wav", language="af", beam_size=5)
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for s in segments:
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print(s.text)
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```
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Pass `language="af"`; the Fluister models are tuned for Afrikaans and SA English and should be told
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the language rather than relying on auto-detect.
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## Limitations
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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.
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**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`.
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## Licence and attribution
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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`.
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