Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use akashmaggon/vit-base-age-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akashmaggon/vit-base-age-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="akashmaggon/vit-base-age-classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("akashmaggon/vit-base-age-classification") model = AutoModelForImageClassification.from_pretrained("akashmaggon/vit-base-age-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from akashmaggon/vit-base-age-classification: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/akashmaggon/vit-base-age-classification/resolve/main/training_args.bin
- Command line
-
hf download hf://akashmaggon/vit-base-age-classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/akashmaggon/vit-base-age-classification/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- fabd8d775c0230193c879039879847098c83dfc8f8e5109e3f653f1ce96ca72f
- Size of remote file:
- 4.6 kB
- SHA256:
- d71937760213e437781f6fe80330fc0491399186fc2a8167835ad5b3fc8cf71d
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