Clay
Clay Foundation Model is an open-source foundational model of Earth. It uses an expanded visual transformer upgraded to understand geospatial and temporal relations on Earth data. The model is trained as a self-supervised Masked Autoencoder (MAE).
The Clay model can be used in three main ways:
- Generate semantic embeddings for any location and time.
- Fine-tune the model for downstream tasks such as classification, regression, and generative tasks.
- Use the model as a backbone for other models.
To load the model to use, see the code below:
module load gfms
module load Clay
With using python, the model could then be accessed via $MODEL_DIR (as below)
>>> import os
>>> model_path = os.getenv("MODEL_DIR")
>>> model_path
'/apps/gfms/Clay'
>>> from claymodel.datamodule import ClayDataModule
>>> from claymodel.module import ClayMAEModule
>>> model = ClayMAEModule.load_from_checkpoint(model_path + "/clay-v1.5.ckpt")
The model could also be used with jupyter notebook, see the code below and then use select kernel named "gfms_clay":
module load jupyter
module load gfms
module load Clay
Then start jupyter notebook in a interactive job by running:
jupyter notebook
Note the module jupyter must be loaded before Clay to have the gfms_clay kernel to be found. The model could also be accessed via $MODEL_DIR.