The HF Text Summarization deep learning package seamlessly integrates pretrained text summarization models from the Hugging Face Hub with ArcGIS, allowing you to generate concise summaries from unstructured text stored in your datasets. With this package, you can transform lengthy text passages—such as survey responses, incident reports, or citizen feedback—into clear and informative summaries that preserve the original meaning and context.
The deep learning package is compatible with a wide range of Hugging Face models for Summarization tasks. Before running a model, ensure compliance with its licensing terms, which are listed on the Hugging Face model page. Use only trusted models, as they include weights and code that could impact system security. Since model sizes vary, confirm that adequate CPU/GPU memory is available for inference.
Model details
This model has the following characteristics:
- Input—A feature class or table containing text.
- Output—A new column with the summary for the input text.
- Compute—This workflow is compute intensive, and a GPU with a minimum CUDA compute capability of 6.0 is recommended.
- Architecture—Uses a Hugging Face pretrained model tagged with Summarization, identified by its model ID.
Access and download the model
Download the HF Text Summarization pretrained model from ArcGIS Living Atlas of the World. Alternatively, access the model directly from ArcGIS Pro using the Transform Text Using Deep Learning tool 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 Text Summarization 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, or upload and use it in ArcGIS Enterprise.
Release notes
The following are the release notes:
| Date | Description |
|---|---|
| September 2025 | First release of HF Text Summarization model |