Audio Classification
Transformers
PyTorch
hubert
Speech Emotion Recognition
SER
Transformer
HuBERT
Affective Computing
custom_code
Instructions to use amiriparian/ExHuBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amiriparian/ExHuBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="amiriparian/ExHuBERT", trust_remote_code=True)# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("amiriparian/ExHuBERT", trust_remote_code=True) model = AutoModelForAudioClassification.from_pretrained("amiriparian/ExHuBERT", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#5 opened over 1 year ago
by
SFconvertbot
Adding `safetensors` variant of this model
#3 opened over 1 year ago
by
SFconvertbot