Audio Classification
Transformers
PyTorch
multilingual
wav2vec2
voice
classification
vocalization
speech
audio
Instructions to use padmalcom/wav2vec2-large-nonverbalvocalization-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use padmalcom/wav2vec2-large-nonverbalvocalization-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="padmalcom/wav2vec2-large-nonverbalvocalization-classification")# Load model directly from transformers import AutoProcessor, Wav2Vec2ForSpeechClassification processor = AutoProcessor.from_pretrained("padmalcom/wav2vec2-large-nonverbalvocalization-classification") model = Wav2Vec2ForSpeechClassification.from_pretrained("padmalcom/wav2vec2-large-nonverbalvocalization-classification") - Notebooks
- Google Colab
- Kaggle
Where does from Wav2Vec2ForSpeechClassification model class come from?
1
#2 opened almost 2 years ago
by
z3ugma
Adding `safetensors` variant of this model
#1 opened almost 3 years ago
by
SFconvertbot