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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6cf10b367f02e40da6264733554fa27f817d978759074a9deb2db0122b017543
- Size of remote file:
- 3.57 kB
- SHA256:
- 2202e8818f5cc0a76070cf40fd540818f8703cf51208930c65e974c6fd97f734
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.