Instructions to use MIbrahimAI/Wav2Vec-SER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MIbrahimAI/Wav2Vec-SER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="MIbrahimAI/Wav2Vec-SER")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("MIbrahimAI/Wav2Vec-SER") model = AutoModelForAudioClassification.from_pretrained("MIbrahimAI/Wav2Vec-SER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9acd2ab0ed3c7fe0368e7c360a854ac0e86c303ad98da2fcdb68e676ef55252a
- Size of remote file:
- 5.2 kB
- SHA256:
- 7d01161d08852ca458ecde01ad46ed610fce44a538ff79c7da5f9397cc4ebcff
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