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
Update README.md
#3
by Rucy - opened
README.md
CHANGED
|
@@ -6,12 +6,12 @@ datasets:
|
|
| 6 |
- fairface
|
| 7 |
---
|
| 8 |
|
| 9 |
-
|
| 10 |
|
| 11 |
A vision transformer finetuned to classify the age of a given person's face.
|
| 12 |
|
| 13 |
|
| 14 |
-
|
| 15 |
|
| 16 |
```python
|
| 17 |
import requests
|
|
|
|
| 6 |
- fairface
|
| 7 |
---
|
| 8 |
|
| 9 |
+
|
| 10 |
|
| 11 |
A vision transformer finetuned to classify the age of a given person's face.
|
| 12 |
|
| 13 |
|
| 14 |
+
|
| 15 |
|
| 16 |
```python
|
| 17 |
import requests
|