Instructions to use makhataei/Wav2vec2-xlsr-Shemo-Ravdess-4EMO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use makhataei/Wav2vec2-xlsr-Shemo-Ravdess-4EMO with Transformers:
# Load model directly from transformers import AutoProcessor, Wav2Vec2ForSpeechClassification processor = AutoProcessor.from_pretrained("makhataei/Wav2vec2-xlsr-Shemo-Ravdess-4EMO") model = Wav2Vec2ForSpeechClassification.from_pretrained("makhataei/Wav2vec2-xlsr-Shemo-Ravdess-4EMO") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- pytorch_model.bin +1 -1
- runs/Aug04_13-08-40_Software-AI/1722764324.0631452/events.out.tfevents.1722764324.Software-AI.2252721.1 +3 -0
- runs/Aug04_13-08-40_Software-AI/events.out.tfevents.1722764324.Software-AI.2252721.0 +3 -0
- runs/Aug04_13-14-27_Software-AI/1722764670.5113697/events.out.tfevents.1722764670.Software-AI.2258800.1 +3 -0
- runs/Aug04_13-14-27_Software-AI/events.out.tfevents.1722764670.Software-AI.2258800.0 +3 -0
- training_args.bin +1 -1
pytorch_model.bin
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training_args.bin
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