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)
Models can be saved with pickle or joblib. The saved object includes the
.omle model bytes, so loading it does not require the original file. Loading
recreates the native model with the original thread settings.
import joblib
joblib.dump(model, "model.joblib")
model = joblib.load("model.joblib")
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 0.2.0rc1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
Total release size: 134.8 MB
Release files / omle_runtime-0.2.0rc1-cp314-cp314-win_amd64.whl
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twine/7.0.0 CPython/3.13.14
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Transparency logRelease files / omle_runtime-0.2.0rc1-cp310-cp310-macosx_11_0_arm64.whl
| Download URL | omle_runtime-0.2.0rc1-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 |
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Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
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