Instructions to use cloudwalkerw/facebook_wav2vec2-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cloudwalkerw/facebook_wav2vec2-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="cloudwalkerw/facebook_wav2vec2-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("cloudwalkerw/facebook_wav2vec2-base") model = AutoModelForAudioClassification.from_pretrained("cloudwalkerw/facebook_wav2vec2-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 205 Bytes
7d1d382 | 1 2 3 4 5 6 7 8 | {
"epoch": 9.98,
"eval_accuracy": 0.8974400257607471,
"eval_loss": 0.4227793216705322,
"eval_runtime": 491.8427,
"eval_samples_per_second": 50.512,
"eval_steps_per_second": 25.256
} |