Instructions to use chaurAr/speech_emotion_det_x with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chaurAr/speech_emotion_det_x with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="chaurAr/speech_emotion_det_x")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("chaurAr/speech_emotion_det_x") model = AutoModelForAudioClassification.from_pretrained("chaurAr/speech_emotion_det_x") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e3486269bf28fe0bc7a39448f707fe869a13cd05e68c8b68f5c1308bfd58a2dc
- Size of remote file:
- 5.71 kB
- SHA256:
- 86469493f99d3d0b20eb632406722078f0a3884e73a78093de2c2cfd1cbe1ad7
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