Instructions to use nateraw/vit-age-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nateraw/vit-age-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nateraw/vit-age-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("nateraw/vit-age-classifier") model = AutoModelForImageClassification.from_pretrained("nateraw/vit-age-classifier") - Inference
- Notebooks
- Google Colab
- Kaggle
Paper reference
Hi,
Thank you for sharing your model! I would like to ask you if you have a publication or a technical report we can cite in our works.
Hi, I realize this is a very late answer, but answering in case others run into this discussion. There is no paper associated with this model, I just trained it in my free time. You can cite this model with the model URL. The dataset used was fairface.
If there's a better way for me to let you cite this, please feel free to suggest it and I can add it to the readme or something :)
Thank you for the answer, at the end we managed to refer to the model through the URL. Now, you have the option to add a DOI if you want.
It would be great to have a video explaining how to train your own model with VIT.
hi can i use the code for my paper publication just want know that
can you reply can i fine tune and use for my project paper
@verarsheuck sure