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AI 모델 535

• whisper-small↗

  unsloth

• whisper-tiny↗

  FL33TW00D-HF

• asr-whisper-large-v3-salt↗

  reuben256

• whisper-large-v3-quantized.w8a8↗

  RedHatAI

• glm-4-voice-tokenizer↗

  zai-org

  GLM-4-Voice is an end-to-end voice model launched by Zhipu AI. GLM-4-Voice can directly understand and generate Chinese and English speech, engage in real-time voice conversations, and change attributes such as emotion, intonation, speech rate, and dialect based on user instructions. 本仓库是 GLM-4-Voice 的 speech tokenizer 部分。通过在 Whisper 的 encoder 部分增加 vector quantization 进行训练，将连续的语音输入转化为离散的 token。每秒音频转化为 12.5 个离散 token。 The repo provides the speech tokenzier of GLM-4-Voice, which is trained by adding vector quantization to the encoder part of Whisper and converts continuous speech input into discrete tokens. Each second of audio is converted into 12.5 discrete tokens.

• typhoon-whisper-large-v3-ctc↗

  typhoon-ai

  Word- and character-level **timestamps for Thai**: a 29M character-CTC head on the **frozen** `typhoon-ai/typhoon-whisper-large-v3` encoder (pinned revision `748e8a4`, recorded in `config.json`). One encoder pass gives transcription *and* alignment. It is **both an aligner and a compact ASR model**: it force-aligns given text (a transcript or ASR hypothesis) to word/character timestamps, and its greedy CTC decode transcribes directly (`--transcribe`, no text needed). `standalone_align.py` (bundled) has no other dependencies; the frozen encoder downloads automatically at the pinned revision. Files: `head.safetensors`, `config.json` (architecture + encoder id/revision), `ctc_vocab.json` (80-symbol Thai char vocab v1.0.0).

• tugstugi_bengaliai-asr_whisper-medium↗

  bengaliAI

• whisperkit-coreml↗

  DictionLabs

• whisper-tiny.en-8bit↗

  mlx-community

• whisperfile↗

  cjpais