Instructions to use nielsr/focalnet-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nielsr/focalnet-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nielsr/focalnet-tiny") 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("nielsr/focalnet-tiny") model = AutoModelForImageClassification.from_pretrained("nielsr/focalnet-tiny") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb7ac7c85acac092ecf5842559a380b22372a7241a38352ef6223a807de00d93
- Size of remote file:
- 114 MB
- SHA256:
- e0581238c22e5861094b7878e5127d2598da9918de28266994a8869b5554b9a2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.