Voice Activity Detection
Transformers
Safetensors
PyTorch
firered-vad-stream
feature-extraction
audio
custom_code
Instructions to use MigoXV/firered-vad-stream with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MigoXV/firered-vad-stream with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MigoXV/firered-vad-stream", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| library_name: transformers | |
| tags: | |
| - audio | |
| - voice-activity-detection | |
| - pytorch | |
| - safetensors | |
| base_model: | |
| - FireRedTeam/FireRedVAD | |
| # FireRed VAD Stream | |
| 这是由原始 `FireRedTeam/FireRedVAD/Stream-VAD` 转换得到的标准 Hugging Face 模型仓库。 | |
| 仓库内容: | |
| - `model.safetensors`:流式 VAD 模型权重 | |
| - `config.json`:`firered-vad-stream` 模型配置和 AutoClass 映射 | |
| - `cmvn.ark`:与原始模型一致的 CMVN 统计量 | |
| - `configuration_firered_vad_stream.py` / `modeling_firered_vad_stream.py` / `module_firered_vad_stream.py`:HF remote code | |
| 加载示例: | |
| ```python | |
| from transformers import AutoModel | |
| model = AutoModel.from_pretrained( | |
| "MigoXV/firered-vad-stream", | |
| trust_remote_code=True, | |
| ) | |
| ``` | |