Model Details
Full Model IDsuperb/wav2vec2-base-superb-er
Pipeline / Taskaudio-classification
Librarytransformers
Downloads (all-time)114.7K
Likes18
Last Modified11/4/2021
Author / Orgsuperb
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="superb/wav2vec2-base-superb-er")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerspytorchwav2vec2audio-classificationspeechaudioendataset:superbarxiv:2105.01051license:apache-2.0endpoints_compatibledeploy:azureregion:us
More audio-classification Models
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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
⬇ Downloads114.7K
❤️ Community Likes18
🛠️ Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.