| from jev_omni import load_jev_omni | |
| classifier = load_jev_omni() | |
| # Text. For other modalities, set modality="image"/"audio"/"video" and | |
| # media="/path/to/file". Video is sampled to 16 frames; audio is capped at 30 s. | |
| result = classifier.predict( | |
| state="The meeting starts at 10 AM. It is now 9 AM.", | |
| question="Has the meeting started?", | |
| options=["Yes", "No"], | |
| ) | |
| print(result) | |