> ## Documentation Index > Fetch the complete documentation index at: https://docs.synthefy.com/llms.txt > Use this file to discover all available pages before exploring further. # Nori > Predict on any table in seconds, with no training. **Nori** is a tabular foundation model for **regression** via in-context learning: give it a few labeled rows as context and it predicts new rows in a single forward pass — no task-specific training or fine-tuning. ```python theme={null} from synthefy_nori import NoriRegressor model = NoriRegressor(model="nori-30m") # downloads pretrained weights on first use model.fit(X_train, y_train) # "fit" just stores the labeled context — no training preds = model.predict(X_test) # predictions in a single forward pass ``` ## Choose how to run it Install the open-source package and predict on your own machine. No key, no GPU required. Send rows to our endpoint and get predictions back. No install, no GPU. ## Why Nori Pretrained once; predict in seconds. No per-dataset training loop. Strong predictions from a handful of rows. A full predictive distribution — quantiles and prediction intervals out of the box. A scikit-learn–style `fit` / `predict` estimator. SHAP, partial dependence, and feature selection built in. Locally (open-source, GPU or CPU) or via the hosted API. ## Next steps Pick the right package in one table. Fit and predict in five lines. Set up a key for the hosted API. Email our team.