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
File size: 169 Bytes
e3753fa | 1 2 3 4 5 6 7 | {
"epoch": 32.0,
"train_loss": 0.9127645113251426,
"train_runtime": 39385.6266,
"train_samples_per_second": 19.295,
"train_steps_per_second": 0.161
} |