Instructions to use frncscp/focalnet-small-patacon with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use frncscp/focalnet-small-patacon with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="frncscp/focalnet-small-patacon") 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("frncscp/focalnet-small-patacon") model = AutoModelForImageClassification.from_pretrained("frncscp/focalnet-small-patacon", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a6d3cf7ca770f3b9e7eb7399ab9abf81bddf77b4a6de35784b5601904f51dbb0
- Size of remote file:
- 197 MB
- SHA256:
- 2f9fc7e3ccf142bef081d5c638b4c320eecb8ad81192608a4bf9189385deaf75
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