Image Classification
Transformers
PyTorch
TensorBoard
Safetensors
convnext
vision
Generated from Trainer
Instructions to use davanstrien/convnext-tiny-224-leicester_binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davanstrien/convnext-tiny-224-leicester_binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="davanstrien/convnext-tiny-224-leicester_binary") 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("davanstrien/convnext-tiny-224-leicester_binary") model = AutoModelForImageClassification.from_pretrained("davanstrien/convnext-tiny-224-leicester_binary") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e753e1493e09b8155872a0c9579cea1e0ea4f1066a23ac4621d61bb6b9b125f0
- Size of remote file:
- 111 MB
- SHA256:
- 7804fb396495be60bc72ebd5aeae37f0b9fc7641e4b1817f32eacbb8b7c00d39
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.