Image Classification
Transformers
Safetensors
beit
knowledge_distillation
vision
Generated from Trainer
Instructions to use c14kevincardenas/beit-base-patch16-224_alpha0.7_temp5.0_t2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use c14kevincardenas/beit-base-patch16-224_alpha0.7_temp5.0_t2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="c14kevincardenas/beit-base-patch16-224_alpha0.7_temp5.0_t2") 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("c14kevincardenas/beit-base-patch16-224_alpha0.7_temp5.0_t2") model = AutoModelForImageClassification.from_pretrained("c14kevincardenas/beit-base-patch16-224_alpha0.7_temp5.0_t2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 20.0, | |
| "eval_accuracy": 0.8013833992094862, | |
| "eval_loss": 0.5586743354797363, | |
| "eval_runtime": 32.6262, | |
| "eval_samples_per_second": 31.018, | |
| "eval_steps_per_second": 0.49 | |
| } |