Image Classification
Transformers
PyTorch
Safetensors
beit
vision
Generated from Trainer
Eval Results (legacy)
Instructions to use NTQAI/pedestrian_age_recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NTQAI/pedestrian_age_recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="NTQAI/pedestrian_age_recognition") 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("NTQAI/pedestrian_age_recognition") model = AutoModelForImageClassification.from_pretrained("NTQAI/pedestrian_age_recognition") - Inference
- Notebooks
- Google Colab
- Kaggle
| timestamp,experiment_id,project_name,duration,emissions,energy_consumed,country_name,country_iso_code,region,on_cloud,cloud_provider,cloud_region | |
| 2023-01-09T04:16:19,62af6737-a71e-47e2-a59d-8f5e4546552b,codecarbon,2168.368220806122,0.15662584062475365,0.2143468409392291,Vietnam,VNM,hanoi,N,, | |