This repository provides the official code, datasets, and checkpoints for the Timer family of large time series foundation models (Timer, Timer-XL, Sundial) from Tsinghua University. It implements a decoder-only Transformer architecture pre-trained on the Unified Time Series Dataset (UTSD) using the single-series sequence (S3) format. The code supports fine-tuning and evaluation on three downstream tasks: forecasting, segment-level imputation, and predictive anomaly detection. Data loading modules handle multiple time series formats (CSV, NPZ, TXT) with flexible windowing and scaling. The repository includes shell scripts for reproducible experiments across multiple datasets and data scarcity ratios. It also provides HuggingFace integration for zero-shot forecasting without training. While primarily a research codebase rather than a production application, it is well-structured with clean module separation and reusable components.