Model Details
Full Model IDtiantiaf/wavlm-large-categorical-emotion
Pipeline / Taskaudio-classification
Library—
Downloads (all-time)46.2K
Likes4
Last Modified8/10/2025
Author / Orgtiantiaf
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("audio-classification", model="tiantiaf/wavlm-large-categorical-emotion")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
safetensorsmodel_hub_mixinpytorch_model_hub_mixinaudio-classificationenarxiv:2505.14648base_model:microsoft/wavlm-largebase_model:finetune:microsoft/wavlm-largelicense:openrailregion:us
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Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🤖 Task: audio-classification
This model is designed for the audio-classification task. Explore more models for this use case.
All audio-classification Models →📊 Popularity
⬇ Downloads46.2K
❤️ Community Likes4
🛠️ Requirements
- →Check docs for installation steps.
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.