Instructions to use Jaljalissimo/Verbum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- pyannote.audio
How to use Jaljalissimo/Verbum with pyannote.audio:
from pyannote.audio import Model, Inference model = Model.from_pretrained("Jaljalissimo/Verbum") inference = Inference(model) # inference on the whole file inference("file.wav") # inference on an excerpt from pyannote.core import Segment excerpt = Segment(start=2.0, end=5.0) inference.crop("file.wav", excerpt) - Notebooks
- Google Colab
- Kaggle
| datasets: | |
| - sonatbaltaci/textindiagrams | |
| - agkphysics/AudioSet | |
| - netflix/Vera-Layered-Video-Dataset | |
| - ILSVRC/imagenet-1k | |
| - armand0e/claude-fable-5-claude-code | |
| language: | |
| - en | |
| metrics: | |
| - accuracy | |
| base_model: | |
| - >- | |
| DavidAU/Qwen3.6-40B-Claude-4.6-Opus-Deckard-Heretic-Uncensored-Thinking-NEO-CODE-Di-IMatrix-MAX-GGUF | |
| - deepseek-ai/DeepSeek-V4-Pro-DSpark | |
| - Cannae-AI/Gemini-3.1-pro-Gemma-4-E4B-Distill | |
| - xai-org/grok-2 | |
| - Hack337/ChatGPT-5 | |
| - HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive | |
| new_version: ReadyArt/Heimdallr-v0.02-31B | |
| library_name: pyannote-audio | |