Data and Learning Hub for Science
A simple way to find, share, publish, and run machine learning models and discover training data for science
m = KerasModel()
m.create_model("p1b1-example.h5")
m.set_title("CANDLE Pilot 1 - Benchmark 1")
m.set_name("candle_p1b1") # short name
m.set_domains("genomics","biology","HPC")
from dlhub_sdk.client import DLHubClient
dl = DLHubClient()
dl.publish_servable(m)
from dlhub_sdk.client import DLHubClient
dl = DLHubClient()
data = np.load("pilot1.npy")
pred = dl.run("test/candle_p1b1", data)
If you find DLHub useful in your research, please cite the following papers:
This material is based upon work supported by Laboratory Directed Research and Development (LDRD) funding from Argonne National Laboratory, provided by the Director, Office of Science, of the U.S. Department of Energy under Contract No. DE-AC02-06CH11357.
© 2020, Argonne National Laboratory