Image Classification
Transformers
TensorBoard
Safetensors
English
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use MattyB95/VIT-ASVspoof2019-Mel_Spectrogram-Synthetic-Voice-Detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MattyB95/VIT-ASVspoof2019-Mel_Spectrogram-Synthetic-Voice-Detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="MattyB95/VIT-ASVspoof2019-Mel_Spectrogram-Synthetic-Voice-Detection") 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("MattyB95/VIT-ASVspoof2019-Mel_Spectrogram-Synthetic-Voice-Detection") model = AutoModelForImageClassification.from_pretrained("MattyB95/VIT-ASVspoof2019-Mel_Spectrogram-Synthetic-Voice-Detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 3.0, | |
| "train_loss": 0.010893226607249389, | |
| "train_runtime": 2856.1574, | |
| "train_samples_per_second": 26.658, | |
| "train_steps_per_second": 3.333 | |
| } |