OlmoEarth — Foundation Model Embeddings for Paper Table 2 This dataset contains pre extracted embeddings from 26 Earth observation foundation models evaluated on the 24 downstream tasks that make up Table 2 of the OlmoEarth paper: OlmoEarth: Stable Latent Image Modeling for Multimodal Earth Observation AI2, 2025. arXiv:2511.13655. For every supported (model, task) pair we ran the model's encoder over the task's train / validation / test splits with the paper best hyperparameters (val best from the original sweep, captured in eval settings/ ). Each split is saved to disk as a single .pt file so downstream KNN / linear probe / fine tuning experiments can skip re extraction. Total size on disk is ~1.1 TB. Layout Each .pt file is a Python dict produced by torch.save : Classification tasks : embeddings is (N, D) . labels is (N,) for single label tasks, (N, num classes) for the multilabel m bigearthnet . Segmentation tasks : embeddings is (N, H, W, D) at the model's patch grid (e.g. (N, 16, 16, 768) for a 64×64 input with stride 4). labels is at full image resolution, e.g. (N, 64, 64) or (N, 256, 256) — the LP head upsamples patch logits to label resolution. D varies by model (128 for th…
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