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")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("microsoft/focalnet-tiny") model = AutoModelForImageClassification.from_pretrained("microsoft/focalnet-tiny", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
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Add hidden_sizes config attribute (#1)
- Add hidden_sizes config attribute (a92a537bb5905e1a82d040ac64d97d4aabbb5941) Co-authored-by: Alara Dirik <adirik@users.noreply.huggingface.co>20d638e
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Create README.md
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Upload processor
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Upload FocalNetForImageClassification
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initial commit
Alara Dirike328e37