Audio Classification
Transformers
PyTorch
TensorBoard
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use anderloh/testV4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anderloh/testV4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="anderloh/testV4")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("anderloh/testV4") model = AutoModelForAudioClassification.from_pretrained("anderloh/testV4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 89
Browse files
pytorch_model.bin
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runs/Jun21_12-13-19_ml6.hpc.uio.no/events.out.tfevents.1718964816.ml6.hpc.uio.no.8934.0
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