Merge pull request #62 from databricks-industry-solutions/integrate_t…

…imegpt

Integrate timegpt

README.md

@@ -226,9 +226,9 @@ MMF is fully integrated with MLflow and so once the training kicks off, the expe
 
 We encourage you to read through [examples/foundation_daily.py](https://github.com/databricks-industry-solutions/many-model-forecasting/blob/main/examples/foundation_daily.py) notebook to better understand how foundation models can be applied to your time series using MMF. An example notebook for monthly forecasting can be found in [examples/foundation_monthly.py](https://github.com/databricks-industry-solutions/many-model-forecasting/blob/main/examples/foundation_monthly.py).
 
-#### Using Foundation Models on Databricks
+#### Using Time Series Foundation Models on Databricks
 
-If you want to try out open source foundation models on Databricks without MMF, you can find example notebooks in [examples/foundation-model-examples](https://github.com/databricks-industry-solutions/many-model-forecasting/tree/main/examples/foundation-model-examples). These notebooks will show you how you can load, distribute the inference, fine-tune, register, deploy a model and generate online forecasts on it. We have notebooks for Chronos, Moirai, Moment, and TimesFM.
+If you want to try out time series foundation models on Databricks without MMF, you can find example notebooks in [examples/foundation-model-examples](https://github.com/databricks-industry-solutions/many-model-forecasting/tree/main/examples/foundation-model-examples). These notebooks will show you how you can load, distribute the inference, fine-tune, register, deploy a model and generate online forecasts on it. We have notebooks for [TimeGPT](https://docs.nixtla.io/), [Chronos](https://github.com/amazon-science/chronos-forecasting), [Moirai](https://github.com/SalesforceAIResearch/uni2ts), [Moment](https://github.com/moment-timeseries-foundation-model/moment), and [TimesFM](https://github.com/google-research/timesfm).
 
 ## Project support
 Please note the code in this project is provided for your exploration only, and are not formally supported by Databricks with Service Level Agreements (SLAs). They are provided AS-IS and we do not make any guarantees of any kind. Please do not submit a support ticket relating to any issues arising from the use of these projects. The source in this project is provided subject to the Databricks License. All included or referenced third party libraries are subject to the licenses set forth below.