Llamafile v0.8.13 (and Whisperfile)
Llamafile version 0.8.13 supports the Gemma 2B and Whisper models, allowing users to transcribe audio files. Compatibility requires 16kHz .wav format, with performance improved using GPU on M2 Max.
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The latest release of llamafile (version 0.8.13) introduces support for the Gemma 2B model and significant performance enhancements. It also adds compatibility with the Whisper speech-to-text model, utilizing Georgi Gerganov's C++ implementation of Whisper. Users can set up whisperfile by downloading the executable from GitHub and obtaining the whisper-tiny.en-q5_1.bin model from Hugging Face. The process involves running commands to transcribe audio files, with options to suppress debug output and save transcripts in JSON format. Users are advised to convert audio recordings to 16kHz .wav files using ffmpeg for compatibility. An update indicates that new whisperfiles have been uploaded to Hugging Face, which can automatically resample various audio formats. Performance tests show that transcribing a 10-minute audio file took 11 seconds with the tiny model and 1 minute 49 seconds with the larger Medium model. Utilizing GPU on an M2 Max MacBook Pro significantly reduced CPU usage and improved transcription speed.
- Llamafile v0.8.13 adds support for Gemma 2B and Whisper speech-to-text model.
- Users can transcribe audio files using whisperfile with various command options.
- Audio files must be converted to 16kHz .wav format for compatibility.
- New whisperfiles can automatically resample different audio formats.
- GPU usage can enhance transcription speed and reduce CPU load.
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