Image Classification
Transformers
PyTorch
TensorBoard
convnextv2
Generated from Trainer
Eval Results (legacy)
Instructions to use ahmedALM1221/convnextv2-large-1k-224-finetuned-eurosat-50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahmedALM1221/convnextv2-large-1k-224-finetuned-eurosat-50 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ahmedALM1221/convnextv2-large-1k-224-finetuned-eurosat-50") 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("ahmedALM1221/convnextv2-large-1k-224-finetuned-eurosat-50") model = AutoModelForImageClassification.from_pretrained("ahmedALM1221/convnextv2-large-1k-224-finetuned-eurosat-50", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 12.0, | |
| "total_flos": 8.283619840147513e+18, | |
| "train_loss": 0.8678286689552454, | |
| "train_runtime": 9120.8487, | |
| "train_samples_per_second": 5.119, | |
| "train_steps_per_second": 0.161 | |
| } |