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The model expects a raw audio signal as input and outputs predictions for age in a range of approximately 0...1 (0...100 years) and gender expressing the probababilty for being child, female, or male. In addition, it also provides the pooled states of the last transformer layer. The model was created by fine-tuning Wav2Vec2-Large-Robust on aGender, Mozilla Common Voice, Timit and Voxceleb 2. For this version of the model we trained all 24 transformer layers. An ONNX export of the model is available from doi:10.5281/zenodo.7761387. Further details are given in the associated paper and tutorial.

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基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

musicgen-medium

facebook

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MusicGen is a text-to-music model capable of genreating high-quality music samples conditioned on text descriptions or audio prompts. It is a single stage auto-regressive Transformer model trained over a 32kHz EnCodec tokenizer with 4 codebooks sampled at 50 Hz. Unlike existing methods, like MusicLM, MusicGen doesn't require a self-supervised semantic representation, and it generates all 4 codebooks in one pass. By introducing a small delay between the codebooks, we show we can predict them in parallel, thus having only 50 auto-regressive steps per second of audio. MusicGen was published in Simple and Controllable Music Generation by *Jade Copet, Felix Kreuk, Itai Gat, Tal Remez, David Kant, Gabriel Synnaeve, Yossi Adi, Alexandre Défossez*. Four checkpoints are released: - small - **medium** (this checkpoint) - large - melody

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Flow Music API（APIMart）：只需提示词、风格标签和歌词即可生成完整 AI 歌曲，可输出带人声或纯音乐版本。开通会员，API 调用立省20%起。

kling-text-to-audio

快手 · 可灵

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文生音效

kling-video-to-audio

快手 · 可灵

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视频生音效

Audio Spectrogram Transformer (AST) model fine-tuned on AudioSet. It was introduced in the paper AST: Audio Spectrogram Transformer by Gong et al. and first released in this repository. Disclaimer: The team releasing Audio Spectrogram Transformer did not write a model card for this model so this model card has been written by the Hugging Face team. The Audio Spectrogram Transformer is equivalent to ViT, but applied on audio. Audio is first turned into an image (as a spectrogram), after which a Vision Transformer is applied. The model gets state-of-the-art results on several audio classification benchmarks.

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bigvgan_v2_22khz_80band_256x

NVIDIA

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- **Jul 2024 (v2.3):** - General refactor and code improvements for improved readability. - Fully fused CUDA kernel of anti-alised activation (upsampling + activation + downsampling) with inference speed benchmark. - **Jul 2024 (v2.2):** The repository now includes an interactive local demo using gradio. - **Jul 2024 (v2.1):** BigVGAN is now integrated with 🤗 Hugging Face Hub with easy access to inference using pretrained checkpoints. We also provide an interactive demo on Hugging Face Spaces.

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bigvgan_v2_44khz_128band_512x

NVIDIA

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基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

gpt-4o-audio-preview

OpenAI

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gpt-4o-audio-preview-2024-10-01

OpenAI

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gpt-4o-audio-preview-2024-12-17

OpenAI

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gpt-4o-audio-preview-2025-06-03

OpenAI

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gpt-4o-mini-audio-preview

OpenAI

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gpt-4o-mini-audio-preview-2024-12-17

OpenAI

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gpt-audio-2025-08-28

OpenAI

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gpt-audio-mini-2025-10-06

OpenAI

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GGUF conversion of OpenMOSS-Team/MOSS-Music-8B-Instruct for **HOT-Step CPP**, a fully local desktop app for AI music generation with a native C++/GGML engine. As far as we know this is the first GGUF conversion of this model. Unlike everything else HOT-Step ships, this model **analyses** audio rather than generating it. It listens to a track and writes a caption describing what it hears — used in HOT-Step's Training Studio to caption your own dataset locally, with no API key and nothing leaving the machine. These files are downloaded automatically by HOT-Step's Model Manager. They are **not** usable with llama.cpp alone: `moss-lm-*.gguf` is structurally a Qwen3 GGUF, but captioning requires the audio tower in `moss-aud-f16.gguf` and the deepstack injection wiring implemented in HOT-Step's engine.

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基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

Suno API（APIMart）：通过一个按量付费 API 即可生成带人声的完整歌曲，并支持歌词创作、音轨分离、翻唱与混音。开通会员，API 调用立省20%起。

suno-act-midi

Suno

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基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。