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Inflect Nano v1

Inflect-Nano-v1 is a tiny English text-to-speech model with 4.63M total inference parameters, including its vocoder.

TipoOtherVersãoRevision ab03027Bnota

Fonte do modelo

Tipo
Other
Tamanho do arquivo
4,55–13,3 MB
Versão
vRevision ab03027
Atualizado
25 de set. de 2026
Downloads
0
Fonte
Hugging Face

Trecho da fonte

Inflect-Nano-v1 is a tiny English text-to-speech model with 4.63M total inference parameters, including its vocoder.

Fontes

1 fonte
Hugging FacePrimárioVersão ab0302781cb0cb9969a9a28ce8e1b259539275dd
huggingface.co/owensong/Inflect-Nano-v1/tree/ab0302781cb0cb9969a9a28ce8e1b259539275dd

Verificado 6 de set.

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Artefatos de modelo

2 artefatos

weights/inflect_nano_v1_acoustic.pt

pt · 13,3 MB · SHA-256 0129f730a25a…ec89 · Hugging Face

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weights/inflect_nano_v1_vocoder.pt

pt · 4,55 MB · SHA-256 57482bee18ef…8d08 · Hugging Face

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Trechos de fonte

2 trechos

--- license: apache-2.0 language: - en tags: - text-to-speech - tts - speech-synthesis - pytorch - ultra-small - local-tts - efficient-inference - experimental pipeline_tag: text-to-speech library_name: pytorch --- <p align="center"> <img src="https://huggingface.co/owensong/Inflect-Nano-v1/resolve/main/assets/inflect-nano-banner.png" alt="Inflect-Nano banner" width="100%"> </p> # Inflect-Nano-v1 **Inflect-Nano-v1 is a tiny English text-to-speech model with 4.63M total inference parameters, including its vocoder.** It is not trying to beat large TTS models. It is a small, local, complete text-to-waveform stack built to test how far ultra-lightweight speech synthesis can go. ## Highlights - **4.63M parameters total** - **Includes the vocoder** - **24 kHz audio** - **Single English male voice** - **Runs locally with PyTorch** - Built for tiny-model experiments, local assistants, embedded demos, and efficient inference research ## Listen | Text | Audio | |---|---| | "Did the timing change?" she answered. "Then why did Logan leave?" | <audio controls preload="none" src="https://huggingface.co/owensong/Inflect-Nano-v1/resolve/main/examples/example_01.wav"></audio> | | Who puts a parking meter next to an ER label? | <audio controls preload="none" src="https://huggingface.co/owensong/Inflect-Nano-v1/resolve/main/examples/example_02.wav"></audio> | | Please say neighborhood, statistics, and anesthesiologist clearly, without rushing through the middle syllables. | <audio controls preload="none" src="https://huggingface.co/owensong/Inflect-Nano-v1/resolve/main/examples/example_03.wav"></audio> | | I said 91, not 306, which is a very different number. | <audio controls preload="none" src="https://huggingface.co/owensong/Inflect-Nano-v1/resolve/main/examples/example_04.wav"></audio> | | The inference path looked natural, but the decoder still needed a smoother transition before Marcus approved the final test. | <audio controls preload="none" src="https://huggingface.co/owensong/Inflect-Nano-v1/resolve/main/examples/example_05.wav"></audio> | | The appointment moved to 1:25, the invoice was $674.96, and the archive was labeled 1998. | <audio controls preload="none" src="https://huggingface.co/owensong/Inflect-Nano-v1/resolve/main/examples/example_06.wav"></audio> | | If Logan sounded uneasy, then it happened near Long Beach, and the pause has to carry that. |...

Source context: 0 downloads · 225 likes · Pipeline text-to-speech · Library pytorch · Repo owensong/Inflect-Nano-v1