Skip to content

Quickstart

This page loads a published Rem3Di model and turns a small dataset of molecules into descriptor vectors.

Prerequisites

  • Installed remedi.
  • A published model directory (see layout).
  • A MoleculeDataset (zarr) to embed. Don't have one? See Prepare a dataset, or use one of the example datasets.

Get descriptors

RemediCalculator goes from a model directory to descriptors: it loads the checkpoint and embeds a dataset for you.

from remedi.evaluation.benchmark.descriptors import RemediCalculator
from remedi.data_handling.dataset.molecule_dataset import MoleculeDataset

# 1. Point the calculator at a published model directory.
calc = RemediCalculator(
    model_dir="/path/to/published_model",
    device="cuda",  # or "cpu"
)

# 2. Open a dataset and embed it.
dataset = MoleculeDataset.open_existing_dataset_from_dir(
    "/path/to/dataset_zarr"
)
descriptors = calc.calculate(dataset)   # numpy array (N_molecules, D)

print(descriptors.shape)

descriptors has one row per molecule; feed it straight into any downstream model.

Running on a different machine than the model was trained on? The MACE path baked into the config may not exist locally, so pass RemediCalculator(model_dir=..., mace_model_path="/local/MACE.model"). See Concepts: Foundation-model frontend.

Next steps