Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use Wiam/wav2vec2-lg-xlsr-en-speech-emotion-recognition-finetuned-babycry-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wiam/wav2vec2-lg-xlsr-en-speech-emotion-recognition-finetuned-babycry-v0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Wiam/wav2vec2-lg-xlsr-en-speech-emotion-recognition-finetuned-babycry-v0")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Wiam/wav2vec2-lg-xlsr-en-speech-emotion-recognition-finetuned-babycry-v0") model = AutoModelForAudioClassification.from_pretrained("Wiam/wav2vec2-lg-xlsr-en-speech-emotion-recognition-finetuned-babycry-v0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3a6fe208e1fc247c221dfc8c33fc3d1e253a1bb21ea507ea075bd7960ee5701d
- Size of remote file:
- 5.3 kB
- SHA256:
- 221ba53708fc7772606b69d769161e3139cf74494b518715d7a14b65d5f6a5f5
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