Instructions to use ibm-esa-geospatial/TerraMind-1.0-Tokenizer-DEM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TerraTorch
How to use ibm-esa-geospatial/TerraMind-1.0-Tokenizer-DEM with TerraTorch:
from terratorch.registry import BACKBONE_REGISTRY model = BACKBONE_REGISTRY.build("ibm-esa-geospatial/TerraMind-1.0-Tokenizer-DEM") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 600bc3334e7848ea9fe4db7596f299cfd304baf76543222865bc8510ebfcc5a0
- Size of remote file:
- 1.18 MB
- SHA256:
- 23c9ec9c371bc3f7b954edec53e60b60079d11087e77fb334aba745fb81a2860
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.