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 | |
| 1,0.47701140120625496,0.27136044204235077 | |
| 2,0.23053773492574692,0.14618618041276932 | |
| 3,0.15947299357503653,0.18215838074684143 | |
| 4,0.14106942061334848,0.10485737025737762 | |
| 5,0.10757852531969547,0.06512117385864258 | |
| 6,0.08166468795388937,0.06458092108368874 | |
| 7,0.05907565797679126,0.04530151002109051 | |
| 8,0.05296348361298442,0.08381620422005653 | |
| 9,0.030643414589576423,0.05677217058837414 | |
| 10,0.02560428116703406,0.046924264170229435 | |
| 11,0.02832902316004038,0.04248674865812063 | |
| 12,0.04046634410042316,0.04350257199257612 | |
| 13,0.039843140286393464,0.04167834855616093 | |
| 14,0.04443829064257443,0.04984385333955288 | |
| 15,0.0256515754153952,0.042679313570261 | |
| 16,0.01758114353287965,0.04563109390437603 | |
| 17,0.018423314642859623,0.04632285609841347 | |
| 18,0.012032014259602875,0.05606958921998739 | |
| 19,0.02342665100877639,0.057493677362799644 | |
| 20,0.013762574351858348,0.028420954942703247 | |