Downloads · 30 days
351
73% of all-time downloads
sled-s2-ls
geohai/sled-s2-ls
sled-s2-ls is a machine learning model from geohai. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This model has been pushed to the Hub using the PytorchModelHubMixin integration: - Code: https://github.com/geohai/sled - Paper: [More Information Needed] - Docs: https://github.com/geohai/sled
All-time downloads
479
Public
Parameters
14.2M
56.7 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors56.7 MB · 100%
At a glance
- Access
- Public
- Created
- Jun 18, 2026
- Updated
- Jun 23, 2026
- SHA
- d0b4a276
Model card
From the Hugging Face model README
This model has been pushed to the Hub using the PytorchModelHubMixin integration:
- Code: https://github.com/geohai/sled
- Paper: [More Information Needed]
- Docs: https://github.com/geohai/sled
This version of SLED embeds in 768 dimensions and uses the RFF position encoder popularized by GeoCLIP. It is trained on
- 50k UAR Sentinel-2 L2A images from the S2-100K dataset
- 50k random Landsat 8/9 OLI_SR images from the SSL4EO dataset
It trains against the following teacher encoders
- Terra-FM for Sentinel-2 imagery
- TorchGeo's Landsat_OLI_SR MOCO model for Landsat 8/9 imagery
- FG-MAE for Sentinel-1 imagery
To load these weights, run the following:
from sled_geo import get_encoder
my_sled_model = get_encoder.get_rff_encoder(embed_dim=768)
my_sled_model.from_pretrained("geohai/sled-s1-s2-ls")
new_york_location = torch.tensor([[-73.935242, 40.730610]]) #lon,lat
my_sled_model(new_york_location) #returns a tensor of [1, 768] shape
- Created
- Jun 18, 2026
- Updated
- Jun 23, 2026