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:
- 3fe44de182314ef02a639bae151e1581b36f807dba0f505c8a78dc2bfcf432da
- Size of remote file:
- 1.38 kB
- SHA256:
- 60bd46f44df0a2036f345adccb6909d082c0596a6254de814418ce2ea26ba4db
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