Model Details
Full Model IDspeechbrain/emotion-recognition-wav2vec2-IEMOCAP
Pipeline / Taskaudio-classification
Libraryspeechbrain
Downloads (all-time)604.4K
Likes188
Last Modified7/23/2024
Author / Orgspeechbrain
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="speechbrain/emotion-recognition-wav2vec2-IEMOCAP")
# Run inference
result = pipe("Your input here")
print(result)����� Tags
speechbrainaudio-classificationEmotionRecognitionwav2vec2pytorchendataset:iemocaparxiv:2106.04624license:apache-2.0region: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
⬇ Downloads604.4K
����� Community Likes188
🛠�� Requirements
- →Install: pip install speechbrain
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.