Any-to-Any
Transformers
Safetensors
multilingual
spev
feature-extraction
multimodal
text
audio
image
video
decision-model
choice
qwen3-omni
lora
custom-code
custom_code
Instructions to use SpragAI/SPEV with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SpragAI/SPEV with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SpragAI/SPEV", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 730 Bytes
7381480 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"questions": {
"decision": {
"instructions": "At the end of this conversation audio, has the most recent speaker yielded the floor or are they continuing their turn?",
"criteria": {
"keep_listening": "The most recent speaker is continuing their turn; keep listening.",
"respond": "The most recent speaker has yielded the floor; another speaker can respond."
}
}
},
"temperature": 1.3234945284875692,
"response_threshold": 0.3856703463365996,
"comparison": "strictly greater than",
"scope": "Fixed English turn-taking schema; not a generic Choice threshold",
"temperature_fitted_on": "AMI designated calibration split",
"threshold_selected_on": "AMI development split"
}
|