Instructions to use anderloh/HuggingfaceTest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anderloh/HuggingfaceTest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="anderloh/HuggingfaceTest")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("anderloh/HuggingfaceTest") model = AutoModelForAudioClassification.from_pretrained("anderloh/HuggingfaceTest") - Notebooks
- Google Colab
- Kaggle
File size: 204 Bytes
d2935d2 | 1 2 3 4 5 6 7 8 | {
"epoch": 323.08,
"eval_accuracy": 0.7027972027972028,
"eval_loss": 0.8156144022941589,
"eval_runtime": 5.0661,
"eval_samples_per_second": 56.453,
"eval_steps_per_second": 0.592
} |