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The HF Zero-Shot Classification deep learning package seamlessly integrates pretrained zero-shot classification models from the Hugging Face Hub with ArcGIS, allowing you to use a variety of Hugging Face zero-shot classification models directly from ArcGIS. With this deep learning package, you can classify objects by providing any class label while running the model. The deep learning package is compatible with a wide range of Hugging Face models for zero-shot image classification tasks.
Before running a model, ensure compliance with its licensing terms, which can be found on the Hugging Face model page. Run only trusted models, as they include weights and code that could impact system security. Since model sizes vary, ensure adequate CPU/GPU memory is available for inference.
Model overview
This model has the following characteristics:
- Input—8-bit RGB imagery.
- Output—Feature class with information about classification of the image.
- Compute—This workflow is compute-intensive, and a GPU with a minimum CUDA compute capability of 6.0 is recommended.
- Applicable geographies—This model is expected to work well globally.
- Architecture—This deep learning package uses the architecture of the chosen HF Zero-Shot Classification model.
Access and download the model
Download the HF Zero-Shot Classification pretrained model from ArcGIS Living Atlas of the World. Alternatively, access the model directly from ArcGIS Pro, or consume it in ArcGIS Image for ArcGIS Online.
- Browse to ArcGIS Living Atlas of the World.
- Sign in with your ArcGIS Online credentials.
- Search for HF Zero-Shot Classification and open the item_page from the search results.
- Click the Download button to download the model.
You can use the downloaded .dlpk file directly in ArcGIS Pro.
Release notes
The following are the release notes:
Date | Description |
---|---|
February 2025 | First release of HF Zero-Shot Classification |