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@@ -60,7 +60,7 @@ getting started [notebook](https://github.com/IBM/tsfm/blob/main/notebooks/hfdem
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  - **512-96-r2**: Given the last 512 time-points (i.e. context length), this model can forecast up to next 96 time-points (i.e. forecast length)
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  in future. This model is pre-trained with a larger pretraining dataset for improved accuracy. Recommended for hourly and minutely
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- resolutions (Ex. 10 min, 15 min, 1 hour, etc). (branch name: 512-96-r2) [[Benchmarks]](https://github.com/ibm-granite/granite-tsfm/blob/main/notebooks/hfdemo/tinytimemixer/ttm-r2_benchmarking_512_96.ipynb)
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  - **1024-96-r2**: Given the last 1024 time-points (i.e. context length), this model can forecast up to next 96 time-points (i.e. forecast length)
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  in future. This model is pre-trained with a larger pretraining dataset for improved accuracy. Recommended for hourly and minutely
 
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  - **512-96-r2**: Given the last 512 time-points (i.e. context length), this model can forecast up to next 96 time-points (i.e. forecast length)
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  in future. This model is pre-trained with a larger pretraining dataset for improved accuracy. Recommended for hourly and minutely
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+ resolutions (Ex. 10 min, 15 min, 1 hour, etc). (branch name: main) [[Benchmarks]](https://github.com/ibm-granite/granite-tsfm/blob/main/notebooks/hfdemo/tinytimemixer/ttm-r2_benchmarking_512_96.ipynb)
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  - **1024-96-r2**: Given the last 1024 time-points (i.e. context length), this model can forecast up to next 96 time-points (i.e. forecast length)
66
  in future. This model is pre-trained with a larger pretraining dataset for improved accuracy. Recommended for hourly and minutely