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AI Models 535

• SenseVoiceSmall↗

  FunAudioLLM

  SenseVoice is part of the **FunASR** ecosystem — one industrial-grade open-source toolkit for **ASR · VAD · punctuation · speaker diarization · emotion / event · LLM-ASR**. A Star really helps the project (and keeps you updated): > ⚡ **CPU / edge — no GPU, no Python:** run SenseVoiceSmall as a single self-contained binary via **llama.cpp / GGUF** (like whisper.cpp), with built-in VAD. Prebuilt binaries + one-command model download → SenseVoiceSmall-GGUF · runtime · guide github repo : https://github.com/FunAudioLLM/SenseVoice

• VibeVoice-ASR-BitNet↗

  Microsoft

  **VibeVoice-ASR-BitNet** is a compressed variant of VibeVoice-ASR optimized for **real-time inference on edge CPUs** — no GPU required. Through heterogeneous quantization, the model is compressed from 4.62 GB to **1.58 GB** while achieving **1.6–2.3× faster** inference than Whisper.cpp with real-time capability (RTF ➡️ **Report:** VibeVoice-ASR-BitNet Technical Report ➡️ **Base Model:** microsoft/VibeVoice-ASR This project was conducted by members of Microsoft Research. If you have suggestions, questions, or observe unexpected behavior, please contact us at VibeVoice@microsoft.com.

• ShellWhisperer-1.5B-GGUF↗

  fableforge-ai

• whisper-large-v3-turbo-ONNX↗

  onnx-community

• drama-3-GGUF↗

  sakasegawa

  These files run only in speech.cpp 0.8.8 or later. Their layout is speech.cpp's own, so llama.cpp, LM Studio, Ollama and other programs that read GGUF cannot run them. They are not made, sponsored or endorsed by Fish Audio. Each file holds Fish Audio's Drama 3, a speech model of 35B parameters with 3B active, and its 44.1 kHz codec, converted to GGUF from the official checkpoint. It speaks a text in any of 83 languages as one speaker or as a scene of up to 16, with cues such as `[laughs]` or `[whispers]` written in the text, in voices cloned from recordings and their words or in voices the model chooses, and passes the audio as it makes it. Install speech.cpp (install), then:

• PhoWhisper-large-ct2↗

  kiendt

• music-whisper↗

  laion

• tiny-random-WhisperForConditionalGeneration↗

  onnx-internal-testing

• whisper-tiny.en↗

  Xenova

  If you haven't already, you can install the Transformers.js JavaScript library from NPM using: Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using 🤗 Optimum and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).

• whisper-base↗

  OpenAI

  Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation. Trained on 680k hours of labelled data, Whisper models demonstrate a strong ability to generalise to many datasets and domains **without** the need for fine-tuning. Whisper was proposed in the paper Robust Speech Recognition via Large-Scale Weak Supervision by Alec Radford et al from OpenAI. The original code repository can be found here. **Disclaimer**: Content for this model card has partly been written by the Hugging Face team, and parts of it were copied and pasted from the original model card.