Instructions to use microsoft/focalnet-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/focalnet-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/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("microsoft/focalnet-tiny") model = AutoModelForImageClassification.from_pretrained("microsoft/focalnet-tiny") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 012d48d1900d349072c6eeb9963a64bc5d7cc53d6cba7fd455bb74ed299855c5
- Size of remote file:
- 114 MB
- SHA256:
- 2402b2a57a987e53a9cff5f8037656283aa2ae216a1be594307d2ea19b699e3e
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