Image Classification
Transformers
TensorBoard
Safetensors
beit
Generated from Trainer
Eval Results (legacy)
Instructions to use BilalMuftuoglu/beit-base-patch16-224-55-fold2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BilalMuftuoglu/beit-base-patch16-224-55-fold2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="BilalMuftuoglu/beit-base-patch16-224-55-fold2") 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("BilalMuftuoglu/beit-base-patch16-224-55-fold2") model = AutoModelForImageClassification.from_pretrained("BilalMuftuoglu/beit-base-patch16-224-55-fold2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e048db15ad04b923c2e75a6f384f261f7ae09f01d0da10916e68e20ddf4367a1
- Size of remote file:
- 5.05 kB
- SHA256:
- aeb9eb817ec4efc16e5c060dc97d9750cfff1b930362875d646f21bf9333d25b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.