Audio Classification
Transformers
Safetensors
English
wav2vec2
emotion
audio
classification
music
facebook
Instructions to use prithivMLmods/Speech-Emotion-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Speech-Emotion-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="prithivMLmods/Speech-Emotion-Classification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("prithivMLmods/Speech-Emotion-Classification") model = AutoModelForAudioClassification.from_pretrained("prithivMLmods/Speech-Emotion-Classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 69892f179f1d959fbf69eb40d4b1fb400b2faa3b426397d54032da289c75c817
- Size of remote file:
- 988 Bytes
- SHA256:
- 0605c8e8178370db2d62980d895c879215a2449873b33f35503646ee93bdb029
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