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OlmoEarth v1 2 Nano

OlmoEarth-v12-Nano is a ViT-Nano (1.7M parameters) foundation model for remote sensing tasks over Sentinel-1, Sentinel-2, and Landsat images or image time series.

ArtOtherVersionRevision e1f693aBBewertung

Modellquelle

Art
Other
Dateigröße
16,2 MB
Version
vRevision e1f693a
Aktualisiert
10. Okt. 2026
Downloads
3118
Quelle
Hugging Face

Quellenbeschreibung

OlmoEarth-v1_2-Nano is a ViT-Nano (1.7M parameters) foundation model for remote sensing tasks over Sentinel-1, Sentinel-2, and Landsat images or image time series.

It was presented in the paper OlmoEarth v1.2: A more efficient family of OlmoEarth models.

Please see our GitHub and paper for more information about OlmoEarth.

If you are interested in computing embeddings with OlmoEarth, or fine-tuning OlmoEarth for a downstream task, see our tutorials:

The OlmoEarth model is deployed in the OlmoEarth Platform, a solution that enables any organization to leverage our models and accelerate their mission, without requiring deep AI or engineering expertise. Sign up to get updates and partner access.

This model is licensed under the OlmoEarth Artifact License. It is intended for use in accordance with Ai2's Responsible Use Guidelines.

Quellen

1 Quelle
Hugging FacePrimärVersion e1f693ae2a7d5b57871a978e9d09e22d05206747
huggingface.co/allenai/OlmoEarth-v1_2-Nano/tree/e1f693ae2a7d5b57871a978e9d09e22d05206747

Verifiziert 10. Okt.

Modellartefakte

1 Artefakt

weights.pth

pth · 16,2 MB · SHA-256 2773fca48c23…0378 · Hugging Face

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Quellenauszüge

3 Auszüge

--- license: other pipeline_tag: image-feature-extraction --- OlmoEarth-v1_2-Nano is a ViT-Nano (1.7M parameters) foundation model for remote sensing tasks over Sentinel-1, Sentinel-2, and Landsat images or image time series. It was presented in the paper [OlmoEarth v1.2: A more efficient family of OlmoEarth models](https://huggingface.co/papers/2605.20804). Please see our GitHub and paper for more information about OlmoEarth. - GitHub: https://github.com/allenai/olmoearth_pretrain - Paper: https://allenai.org/papers/olmoearth_v1_2 If you are interested in computing embeddings with OlmoEarth, or fine-tuning OlmoEarth for a downstream task, see our tutorials: - [Fine-tuning OlmoEarth for Segmentation using olmoearth_run](https://github.com/allenai/olmoearth_projects/blob/main/docs/tutorials/FinetuneOlmoEarthSegmentation.md) - [Computing OlmoEarth Embeddings](https://github.com/allenai/rslearn/blob/master/docs/examples/OlmoEarthEmbeddings.md) - [Fine-tuning OlmoEarth using rslearn](https://github.com/allenai/rslearn/blob/master/docs/examples/FinetuneOlmoEarth.md) The OlmoEarth model is deployed in [the OlmoEarth Platform](https://olmoearth.allenai.org/), a solution that enables any organization to leverage our models and accelerate their mission, without requiring deep AI or engineering expertise. [Sign up to get updates and partner access.](https://3ioxm.share.hsforms.com/23TW_rZwBSfauI1R3t0tdTQ) This model is licensed under the [OlmoEarth Artifact License](LICENSE.txt). It is intended for use in accordance with Ai2's [Responsible Use Guidelines](https://allenai.org/responsible-use).

Source context: 3118 downloads · 7 likes · Pipeline image-feature-extraction · Repo allenai/OlmoEarth-v1_2-Nano

Source context: 6768 downloads · 5 likes · Pipeline image-feature-extraction · Repo allenai/OlmoEarth-v1_2-Nano