Instructions to use SAP/sap-rpt-1-oss with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sap-rpt-1-oss
How to use SAP/sap-rpt-1-oss with sap-rpt-1-oss:
pip install git+https://github.com/SAP-samples/sap-rpt-1-oss
# Run a classification task from sklearn.datasets import load_breast_cancer from sklearn.metrics import accuracy_score from sklearn.model_selection import train_test_split from sap_rpt_oss import SAP_RPT_OSS_Classifier # Load sample data X, y = load_breast_cancer(return_X_y=True) X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.5, random_state=42) # Initialize a classifier, 8k context and 8-fold bagging gives best performance, reduce if running out of memory clf = SAP_RPT_OSS_Classifier(max_context_size=8192, bagging=8) clf.fit(X_train, y_train) # Predict probabilities prediction_probabilities = clf.predict_proba(X_test) # Predict labels predictions = clf.predict(X_test) print("Accuracy", accuracy_score(y_test, predictions))# Run a regression task from sklearn.datasets import fetch_openml from sklearn.metrics import r2_score from sklearn.model_selection import train_test_split from sap_rpt_oss import SAP_RPT_OSS_Regressor # Load sample data df = fetch_openml(data_id=531, as_frame=True) X = df.data y = df.target.astype(float) # Train-test split X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.5, random_state=42) # Initialize the regressor, 8k context and 8-fold bagging gives best performance, reduce if running out of memory regressor = SAP_RPT_OSS_Regressor(max_context_size=8192, bagging=8) regressor.fit(X_train, y_train) # Predict on the test set predictions = regressor.predict(X_test) r2 = r2_score(y_test, predictions) print("R² Score:", r2) - Notebooks
- Google Colab
- Kaggle
Request: DOI
Hello SAP AI Team,
I am writing to request access to the sap-rpt-1-oss model available on Hugging Face.
I am a software engineer and cybersecurity researcher working on data analysis and anomaly detection projects in enterprise environments. My current research focuses on understanding and modeling structured ERP database schemas, particularly SAP Business One–like relational data, for use in:
schema-aware data analysis
anomaly and pattern detection
semantic understanding of tabular enterprise data
internal testing and proof-of-concept studies
The model will be used strictly in controlled, non-production test environments with anonymized or synthetic data. No customer-identifiable or sensitive production data will be used.
My intention is to evaluate the model’s capability in learning relational patterns from structured tables and to explore fine-tuning approaches on ERP-style schemas for research and internal tooling purposes.
I would be happy to comply with any licensing, usage, or reporting requirements associated with the model.
Thank you for making your work available to the community. I look forward to your response.
Kind regards,
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