Feature Extraction
Transformers
Safetensors
sensevoice_encoder_portable
duplexjev
audio
asr-encoder
sensevoice
custom_code
Instructions to use adventists-ai-research/SenseVoice-Small-Encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adventists-ai-research/SenseVoice-Small-Encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="adventists-ai-research/SenseVoice-Small-Encoder", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("adventists-ai-research/SenseVoice-Small-Encoder", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from adventists-ai-research/SenseVoice-Small-Encoder: direct link, hf CLI and curl.
- Browser
- Download file 347 Bytes
-
https://huggingface.co/adventists-ai-research/SenseVoice-Small-Encoder/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://adventists-ai-research/SenseVoice-Small-Encoder/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/adventists-ai-research/SenseVoice-Small-Encoder/resolve/main/preprocessor_config.json
347 Bytes
| { | |
| "feature_extractor_type": "SenseVoiceWaveFrames", | |
| "auto_map": { | |
| "AutoFeatureExtractor": "feature_extraction_sensevoice.SenseVoiceWaveFrames", | |
| "AutoProcessor": "feature_extraction_sensevoice.SenseVoiceWaveFrames" | |
| }, | |
| "feature_size": 160, | |
| "sampling_rate": 16000, | |
| "hop_length": 160, | |
| "chunk_length": 30, | |
| "padding_value": 0.0 | |
| } |