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Chapter 13. Validated models for geospatial inference with TerraTorch
The following IBM and NASA Prithvi geospatial foundation models are validated for use with AI Inference Server and TerraTorch.
Prithvi-EO-2.0 models use the Vision Transformer (ViT) architecture and require TerraTorch as the model implementation backend. These models accept GeoTIFF imagery as input and return segmentation predictions.
| Model | Use case | Hugging Face model card | Validated on |
|---|---|---|---|
| Prithvi-EO-2.0-300M-TL-Sen1Floods11 | Flood detection and mapping | RHAIIS 3.3 | |
| Prithvi-EO-2.0-300M-BurnScars | Burn scar detection | RHAIIS 3.3 |
Explore the IBM and NASA geospatial models collection on Hugging Face.
Prithvi geospatial models are validated for use with NVIDIA CUDA AI accelerators only.
These models require specific vLLM server arguments to function correctly. You must include --skip-tokenizer-init, --enforce-eager, and --enable-mm-embeds when starting the inference server.
For the complete list of required server arguments, see TerraTorch configuration options for geospatial model serving and Serving TerraTorch Models with vLLM.
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