Audio Classification
Transformers
Safetensors
cue
voice-agent
turn-taking
barge-in
endpointing
full-duplex
indian-english
Instructions to use IOTEverythin/cue-v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IOTEverythin/cue-v5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="IOTEverythin/cue-v5")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("IOTEverythin/cue-v5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download encoder/preprocessor_config.json from IOTEverythin/cue-v5: direct link, hf CLI and curl.
- Browser
- Download file 329 Bytes
-
https://huggingface.co/IOTEverythin/cue-v5/resolve/main/encoder/preprocessor_config.json
- Command line
-
hf download hf://IOTEverythin/cue-v5/encoder/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/IOTEverythin/cue-v5/resolve/main/encoder/preprocessor_config.json
329 Bytes
| { | |
| "chunk_length": 30, | |
| "dither": 0.0, | |
| "feature_extractor_type": "WhisperFeatureExtractor", | |
| "feature_size": 80, | |
| "hop_length": 160, | |
| "n_fft": 400, | |
| "n_samples": 480000, | |
| "nb_max_frames": 3000, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "return_attention_mask": false, | |
| "sampling_rate": 16000 | |
| } | |