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
| { | |
| "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, | |
| "train_loss": 0.8143934268043155, | |
| "train_runtime": 4784.9132, | |
| "train_samples_per_second": 113.231, | |
| "train_steps_per_second": 0.219 | |
| } |