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@@ -75,22 +75,6 @@ getting started [notebook](https://github.com/IBM/tsfm/blob/main/notebooks/hfdem
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  but can provide any forecast lengths up to 720 in get_model() to get the required model.
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- ## Model Capabilities with example scripts
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- The below model scripts can be used for any of the above TTM models. Please update the HF model URL and branch name in the `from_pretrained` call appropriately to pick the model of your choice.
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- **Since these models use frequency prefix tuning, ensure your dataset yaml (as mentioned in the below notebooks) have frequency information and set `enable_prefix_tuning` to True in load_dataset.**
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- - Getting Started [[colab]](https://colab.research.google.com/github/ibm-granite/granite-tsfm/blob/main/notebooks/hfdemo/ttm_getting_started.ipynb)
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- - Zeroshot Multivariate Forecasting [[Example]](https://github.com/ibm-granite/granite-tsfm/blob/main/notebooks/hfdemo/ttm_getting_started.ipynb)
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- - Finetuned Multivariate Forecasting:
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- - Channel-Independent Finetuning [[Example 1]](https://github.com/ibm-granite/granite-tsfm/blob/main/notebooks/hfdemo/ttm_getting_started.ipynb) [[Example 2]](https://github.com/ibm-granite/granite-tsfm/blob/main/notebooks/hfdemo/tinytimemixer/ttm_m4_hourly.ipynb)
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- - Channel-Mix Finetuning [[Example]](https://github.com/ibm-granite/granite-tsfm/blob/main/notebooks/tutorial/ttm_channel_mix_finetuning.ipynb)
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- - **New Releases (extended features released on October 2024)**
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- - Finetuning and Forecasting with Exogenous/Control Variables [[Example]](https://github.com/ibm-granite/granite-tsfm/blob/main/notebooks/tutorial/ttm_with_exog_tutorial.ipynb)
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- - Finetuning and Forecasting with static categorical features [Example: To be added soon]
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- - Rolling Forecasts - Extend forecast lengths via rolling capability. Rolling beyond 2*forecast_length is not recommended. [[Example]](https://github.com/ibm-granite/granite-tsfm/blob/main/notebooks/hfdemo/ttm_rolling_prediction_getting_started.ipynb)
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- - Helper scripts for optimal Learning Rate suggestions for Finetuning [[Example]](https://github.com/ibm-granite/granite-tsfm/blob/main/notebooks/tutorial/ttm_with_exog_tutorial.ipynb)
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  ## Benchmarks
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  <p align="center" width="100%">
 
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  but can provide any forecast lengths up to 720 in get_model() to get the required model.
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  ## Benchmarks
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  <p align="center" width="100%">