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v1.2.1

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@ggerganov ggerganov released this 28 Feb 20:30
· 944 commits to master since this release
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Overview

This is a minor release. The main reason for it is a critical bug fix that causes the software to crash randomly when the language auto-detect option is used (i.e. whisper_lang_auto_detect()).

Other than that, the release includes refactoring of the examples, ruby bindings and some minor changes to the C API.

You can provide feedback in the existing v1.2.0 discussion.

What's Changed

Core ggml / whisper

  • whisper : whisper : add "split_on_word" flag when using using "max_len" option by @mightymatth in #455 and @boolemancer in #476
  • whisper : add whisper_full_lang_id() for getting the context lang by @kamranjon in #461
  • whisper : fixed Beam Search Strategy and exposed whisper_pcm_to_mel_phase_vocoder by @sandrohanea in #474
  • whisper : suppress non-speech-related token outputs by @shibukazu in #473
  • cmake : install whisper.h header by @aviks in #485
  • whisper : fix signedness compiler warning by @shikokuchuo in #506
  • whisper : by default disable non-speech tokens suppression #473
  • whisper : add API for applying custom logits filters during decoding 0d22916
  • whisper : fix uninitialized exp_n_audio_ctx by @finnvoor in #520

Bindings

  • bindings : add Ruby by @taf2 in #500
  • readme : add .NET repos (#303)
  • readme : add cython bindings (#9)
  • readme : add pybind11 bindings by @aarnphm in #538

Examples

  • ci : add node addon test and optimize compilation configuration by @chenqianhe in #468
  • yt-wsp.sh : add unique filename generation by @genevera in #495
  • examples : refactor in order to reuse code and reduce duplication by @ggerganov in #482
  • main : fix stdin pipe stream by @conradg in #503
  • make : add "-mcpu=native" when building for aarch64 (#532)

C-style API

  • Add whisper_pcm_to_mel_phase_vocoder()
  • Add *(whisper_logits_filter_callback)()
  • Change struct whisper_full_params
  • Add whisper_full_lang_id()

New Contributors

Full Changelog: v1.2.0...v1.2.1

Highlights

Recently, I have been making progress on adding integer quantisation support in the ggml tensor library. This will eventually allow to use quantised models which require less memory and will hopefully run faster. I think the next major release v1.3.0 will officially add quantisation support. For now, you can keep track of the progress in #540