You can run a local pickle model via
docker run -i --rm -v "$PWD:$PWD" ghcr.io/numerai/numerai_predict_py_3_10:stable --model $PWD/model.pkl
Presigned GET and POST urls are used to ensure that only the specified model is downloaded during execution and that model prediction uploads from other models are not accessed or tampered with.
The --model
arg is designed to accept a pre-signed S3 GET URL generated via boto3
params = dict(Bucket='numerai-pickled-user-models',
Key='5a5a8da7-05a4-41bf-9c2b-7f61bab5b89b/model-Kc5pT9r85SRD.pkl')
presigned_model_url = s3_client.generate_presigned_url("get_object", params, ExpiresIn=600)
The --post_url
and --post_data
args are designed to accept a pre-signed S3 POST URL + urlencoded data dictionary
generated via boto3
presigned_post = s3_client.generate_presigned_post(Bucket='numerai-pickled-user-models-live-output',
Key='5a5a8da7-05a4-41bf-9c2b-7f61bab5b89b/live_predictions-b7446fc4cc7e.csv',
ExpiresIn=600)
post_url = presigned_post['url']
post_data = urllib.parse.urlencode(presigned_post['fields'])