Aller au contenu
ModelPrésentéExterne
Télécharger

OlmoEarth v1 2 Tiny

OlmoEarth-v12-Tiny is a ViT-Tiny (12M parameters) foundation model for remote sensing tasks over Sentinel-1, Sentinel-2, and Landsat images or image time series.

TypeOtherVersionRevision 12a9fdbBClasse

Source du modèle

Type
Other
Taille du fichier
102 MB
Version
vRevision 12a9fdb
Mis à jour
10 oct. 2026
Téléchargements
1,9 k
Source
Hugging Face

Description de la source

OlmoEarth-v1_2-Tiny is a ViT-Tiny (12M parameters) foundation model for remote sensing tasks over Sentinel-1, Sentinel-2, and Landsat images or image time series.

This model was introduced 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.

Sources

1 source
Hugging FacePrincipalVersion 12a9fdbfeff905d7e147e7497f9f7a95c518eefc
huggingface.co/allenai/OlmoEarth-v1_2-Tiny/tree/12a9fdbfeff905d7e147e7497f9f7a95c518eefc

Vérifié 10 oct.

Artefacts du modèle

1 artefact

weights.pth

pth · 102 MB · SHA-256 835c0b21ab01…697d · Hugging Face

Télécharger

Extraits de sources

3 extraits

--- license: other pipeline_tag: image-feature-extraction --- OlmoEarth-v1_2-Tiny is a ViT-Tiny (12M parameters) foundation model for remote sensing tasks over Sentinel-1, Sentinel-2, and Landsat images or image time series. This model was introduced 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: 1871 downloads · 1 likes · Pipeline image-feature-extraction · Repo allenai/OlmoEarth-v1_2-Tiny

Source context: 1351 downloads · 1 likes · Pipeline image-feature-extraction · Repo allenai/OlmoEarth-v1_2-Tiny