Question: commercial use of SenseVoiceSmall weights under MODEL_LICENSE (Android app, incl. users in China)

Abierto
  • ¿Algo no está bien?
#3,795 0 comentarios 0 reacciones 0 asignados Ver en GitHub

Los mantenedores suelen responder en 1 día

Nadie ha tomado este issue todavía.

Evaluación

Dificultad
1/5
Tiempo estimado
Menos de una hora
Aptitud para principiantes
20/100
Tipo de issue
Documentación
Claridad
Bien especificado
Estado de actividad
Activo
Stack tecnológico
python
Área
documentation

Línea de trabajo

The question concerns SenseVoiceSmall's MODEL_LICENSE and its Hugging Face model card. Start by reviewing the license text and the linked Hugging Face discussion; the issue is resolved when the team clarifies commercial use, redistribution and attribution, and any relevant restrictions.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

needs triage question

Hi FunASR team,

I'm an independent developer building an offline travel interpreter app for Android (Korean / Chinese / Japanese / English). I would like to use SenseVoiceSmall (ONNX int8, run via sherpa-onnx) for fully on-device speech recognition.

The Hugging Face model card lists "license: other / model-license", which points to the MODEL_LICENSE file in this repository. I posted the same question there (https://huggingface.co/FunAudioLLM/SenseVoiceSmall/discussions/18) but have not received an answer yet.

Could you please clarify:

  1. Commercial use: May the SenseVoiceSmall weights be used inside a commercial app (free or paid) distributed through app stores, including to users in mainland China?
  2. Redistribution: May I bundle the converted (ONNX/int8) weights in the app package, or download them on first run? If so, what attribution (model name, source, license text) is required?
  3. Wording of the license: The license text mentions "reference / learning purposes" (section 3). Does this restrict use of the model inside an end-user application?
  4. Are there any restrictions from the training data or other upstream components that I should be aware of?

I only plan to ship the pretrained weights, not any training data. A short written answer here would help me decide whether I can ship it. If this is the wrong place to ask, please point me to the right channel.

Thank you!

Lenguaje dominante
Python
Estrellas
21k
Forks
2.1k
Merge medio
15 h 16 min
PR fusionados (30 d)
85

Preparar el entorno

Primeros pasos

  1. Lee el issue completo y luego la guía de contribución del proyecto.
  2. Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
  3. Haz un fork del repositorio y trabaja en una rama.
  4. Abre un pull request que haga referencia al número del issue.

Más de modelscope/FunASR

Todos los issues de modelscope/FunASR

Issues similares

Más issues de Python

Recibe los nuevos issues en tu correo

Un resumen breve de issues de GitHub para principiantes.