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
metadata
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