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
- Xet hash:
- 320ef31ab7e748f5b25b4b6c66eff4371dd0443667591213060045d34bac148a
- Size of remote file:
- 347 MB
- SHA256:
- 82e962817857e71e644953ae8a458db36db31a3d5293289b6acd5b49317524ad
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