Image Classification
Transformers
Safetensors
mobilevit
knowledge_distillation
vision
Generated from Trainer
Instructions to use c14kevincardenas/mobilevit-small_alpha0.7_temp3.0_t3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use c14kevincardenas/mobilevit-small_alpha0.7_temp3.0_t3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="c14kevincardenas/mobilevit-small_alpha0.7_temp3.0_t3") 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/mobilevit-small_alpha0.7_temp3.0_t3") model = AutoModelForImageClassification.from_pretrained("c14kevincardenas/mobilevit-small_alpha0.7_temp3.0_t3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 20.0, | |
| "eval_accuracy": 0.6616052060737527, | |
| "eval_loss": 0.9566261172294617, | |
| "eval_runtime": 40.9778, | |
| "eval_samples_per_second": 22.5, | |
| "eval_steps_per_second": 0.708, | |
| "total_flos": 0.0, | |
| "train_loss": 0.37087090215305, | |
| "train_runtime": 14479.2181, | |
| "train_samples_per_second": 7.216, | |
| "train_steps_per_second": 0.227 | |
| } |