This release is a pre-release and may not be stable for production use.
omle-runtime
Fast inference for classical ML models, with a scikit-learn-style API.
omle-runtime loads .omle models and scores them through a native C++ runtime
with pybind11 bindings. Wheels are self-contained — protobuf and Abseil are
linked in statically, so there is nothing to install alongside.
import numpy as np
import omle_runtime as omr
model = omr.load("model.omle", n_threads=4) # thread-safe
X = np.random.randn(1000, 10).astype(np.float32)
scores = model.predict(X) # (n_samples,)
proba = model.predict_proba(X) # (n_samples, n_outputs)
Model implements the scikit-learn estimator interface (predict,
predict_proba, fit, get_params, set_params, n_features_in_,
feature_names_in_), so it can be the final step of a Pipeline:
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardScaler
pipe = Pipeline([("scaler", StandardScaler()), ("model", model)])
pipe.predict(X)
For repeated scoring on a thread, create a session once and reuse it:
session = model.create_session() # one per thread
scores = session.predict(X)
Related packages
omle— the model IR and convertersomle-spark— PySpark transformer
License
Apache-2.0
1 maintainer
Release files for omle-runtime 0.1.0rc7
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
Total release size: 134.6 MB
Release files / omle_runtime-0.1.0rc7-cp314-cp314-win_amd64.whl
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
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twine/7.0.0 CPython/3.13.14
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Transparency logRelease files / omle_runtime-0.1.0rc7-cp310-cp310-macosx_11_0_arm64.whl
| Download URL | omle_runtime-0.1.0rc7-cp310-cp310-macosx_11_0_arm64.whl |
|---|---|
| Size | 4.6 MB |
| Tags | CPython 3.10 macOS 11.0+ ARM64 |
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SHA-256 checksum How to use checksums |
6a833b062ba52d8f516c3bb27c4b7a5195118ac8bf12ad415f3c19fc1eae936f
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BLAKE2b-256 checksum How to use checksums |
03977583e6d94825b8c963cb801cc3f5ae4ebf5d65f4f361c4a4bb09db5edee2
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 20, 2026.
Transparency log
