Instructions to use galsenai/wav2vec2-base-waxal-keyword-spotting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use galsenai/wav2vec2-base-waxal-keyword-spotting with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="galsenai/wav2vec2-base-waxal-keyword-spotting")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("galsenai/wav2vec2-base-waxal-keyword-spotting") model = AutoModelForAudioClassification.from_pretrained("galsenai/wav2vec2-base-waxal-keyword-spotting") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 32.0, | |
| "train_loss": 0.9127645113251426, | |
| "train_runtime": 39385.6266, | |
| "train_samples_per_second": 19.295, | |
| "train_steps_per_second": 0.161 | |
| } |