Lag-Llama is an open-source foundation model designed for zero-shot and finetuned probabilistic time series forecasting. It adapts the LLaMA transformer architecture to handle time series data, enabling probabilistic predictions with uncertainty quantification. The model supports zero-shot forecasting out of the box and can be finetuned on specific time series datasets. Model weights are available on HuggingFace.