Instructions to use 100rab25/bridalMakeupClassifier_binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 100rab25/bridalMakeupClassifier_binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="100rab25/bridalMakeupClassifier_binary") 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("100rab25/bridalMakeupClassifier_binary") model = AutoModelForImageClassification.from_pretrained("100rab25/bridalMakeupClassifier_binary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 20.0, | |
| "eval_accuracy": 1.0, | |
| "eval_f1": 1.0, | |
| "eval_loss": 0.00724475271999836, | |
| "eval_precision": 1.0, | |
| "eval_recall": 1.0, | |
| "eval_runtime": 0.6251, | |
| "eval_samples_per_second": 519.879, | |
| "eval_steps_per_second": 17.596, | |
| "total_flos": 1.4530811161131418e+18, | |
| "train_loss": 0.0580909106111073, | |
| "train_runtime": 291.8902, | |
| "train_samples_per_second": 200.281, | |
| "train_steps_per_second": 1.576 | |
| } |