Instructions to use ViTAMIn-O/PDLO_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ViTAMIn-O/PDLO_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ViTAMIn-O/PDLO_classifier") 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("ViTAMIn-O/PDLO_classifier") model = AutoModelForImageClassification.from_pretrained("ViTAMIn-O/PDLO_classifier") - Notebooks
- Google Colab
- Kaggle
| epoch,train_loss,val_loss | |
| 1,0.538878183811903,0.30797648429870605 | |
| 2,0.26180985383689404,0.17218229174613953 | |
| 3,0.1717955470085144,0.13028602302074432 | |
| 4,0.1437947005033493,0.10177387297153473 | |
| 5,0.10723237367346883,0.11121335625648499 | |
| 6,0.08349944278597832,0.11192755028605461 | |
| 7,0.07720590848475695,0.131826750934124 | |
| 8,0.07390826242044568,0.08874695003032684 | |
| 9,0.059899297542870045,0.08273351192474365 | |
| 10,0.07470285997260362,0.08861568570137024 | |
| 11,0.028520599356852472,0.10082890838384628 | |
| 12,0.024814573233015835,0.06342275068163872 | |
| 13,0.037214646697975695,0.09319406375288963 | |
| 14,0.02800476152333431,0.04895220510661602 | |
| 15,0.017185716424137354,0.04200319666415453 | |
| 16,0.05007501703221351,0.06883817911148071 | |
| 17,0.020178327045869082,0.11221175268292427 | |
| 18,0.01919980809907429,0.2134331837296486 | |
| 19,0.02056509326212108,0.0834646187722683 | |
| 20,0.010971037321723998,0.046443226747214794 | |