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 NOTICE from IOTEverythin/cue-v5: direct link, hf CLI and curl.
- Browser
- Download file 1.32 kB
-
https://huggingface.co/IOTEverythin/cue-v5/resolve/main/NOTICE
- Command line
-
hf download hf://IOTEverythin/cue-v5/NOTICE
-
curl -L -o NOTICE https://huggingface.co/IOTEverythin/cue-v5/resolve/main/NOTICE
1.32 kB
| Cue v5 | |
| Copyright 2026 IOTEverythin. Licensed under the Apache License, Version 2.0 (see LICENSE). | |
| Third-party components and data | |
| encoder/ The encoder of OpenAI Whisper small (openai/whisper-small), Apache License 2.0. | |
| Modification: only the encoder is kept and its positional-embedding table is cut to the | |
| first 100 positions (2 seconds of audio). All other weights are unchanged. | |
| cue.safetensors, config.json | |
| Cue head, IOTEverythin. Trained (fine-tuned from Cue v4) on: | |
| - synthetic Indian English calls generated with Chatterbox TTS (Resemble AI, MIT) and, for a | |
| subset of caller lines, Dia-1.6B (Nari Labs, Apache-2.0), with reference voices from GLOBE | |
| (CC0, Mozilla Common Voice) and Svarah (AI4Bharat, CC-BY-4.0); | |
| - the AMI Meeting Corpus (University of Edinburgh, IDIAP, TNO and the AMI Consortium), | |
| Creative Commons Attribution 4.0: https://groups.inf.ed.ac.uk/ami/corpus/ | |
| - the ICSI Meeting Corpus (International Computer Science Institute), Creative Commons | |
| Attribution 4.0: https://groups.inf.ed.ac.uk/ami/icsi/ | |
| - background noise from MUSAN (OpenSLR 17, CC-BY-4.0), in training augmentation only. | |
| No audio from these corpora is included in this repository. | |