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.
Fuente del modelo
- Tipo
- Other
- Tamaño del archivo
- 16,2 MB
- Versión
- vRevision e1f693a
- Actualizado
- 10 oct 2026
- Descargas
- 3,1 mil
- Fuente
- Hugging Face
Descripción de la fuente
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.
- 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
- Computing OlmoEarth Embeddings
- Fine-tuning OlmoEarth using rslearn
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.
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 10 oct
Artefactos del modelo
1 artefacto
Artefactos del modelo
1 artefactoExtractos de fuentes
3 extractos
Extractos de fuentes
3 extractos--- 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
