Audio Classification
Transformers
PyTorch
laughter_detection
laughter-detection
wavlm
speech
humor
stand-up-comedy
genki
Instructions to use Hayasuki/ChuckleNet-Genki with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hayasuki/ChuckleNet-Genki with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Hayasuki/ChuckleNet-Genki")# pip install -U transformers accelerate # Load model directly from transformers import WavLMForLaughterDetection model = WavLMForLaughterDetection.from_pretrained("Hayasuki/ChuckleNet-Genki", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Hayasuki/ChuckleNet-Genki: direct link, hf CLI and curl.
- Browser
- Download file 2.23 MB
-
https://huggingface.co/Hayasuki/ChuckleNet-Genki/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Hayasuki/ChuckleNet-Genki/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Hayasuki/ChuckleNet-Genki/resolve/main/pytorch_model.bin
2.23 MB
- Xet hash:
- 5caf1e332438bcec497b77ae1a21352bf33dabecfd40246755f06cf1a15c733f
- Size of remote file:
- 2.23 MB
- SHA256:
- 2ff08385252a17265dfd11037739fb976fb9a9e582f2916ed66bec6f2403e1f7
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