Instructions to use KaushalB/ViTForMusicClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KaushalB/ViTForMusicClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="KaushalB/ViTForMusicClassification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("KaushalB/ViTForMusicClassification") model = AutoModelForImageClassification.from_pretrained("KaushalB/ViTForMusicClassification") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 20.0, | |
| "eval_accuracy": 0.7354497354497355, | |
| "eval_loss": 0.8083848357200623, | |
| "eval_runtime": 1.8368, | |
| "eval_samples_per_second": 102.896, | |
| "eval_steps_per_second": 6.533 | |
| } |