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Fix training install instructions (#236)
*Issue #, if available:* Fixes #235 *Description of changes:* By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.
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@ -4,7 +4,7 @@
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- Install this package with with the `training` extra:
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```
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pip install "chronos[training] @ git+https://github.com/amazon-science/chronos-forecasting.git"
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pip install "chronos-forecasting[training] @ git+https://github.com/amazon-science/chronos-forecasting.git"
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```
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- Run `kernel-synth.py`:
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```sh
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@ -21,7 +21,7 @@
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## Pretraining (and fine-tuning) Chronos models
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- Install this package with with the `training` extra:
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```
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pip install "chronos[training] @ git+https://github.com/amazon-science/chronos-forecasting.git"
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pip install "chronos-forecasting[training] @ git+https://github.com/amazon-science/chronos-forecasting.git"
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```
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- Convert your time series dataset into a GluonTS-compatible file dataset. We recommend using the arrow format. You may use the `convert_to_arrow` function from the following snippet for that. Optionally, you may use [synthetic data from KernelSynth](#generating-synthetic-time-series-kernelsynth) to follow along.
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```py
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@ -113,7 +113,7 @@ Follow these steps to compute the WQL and MASE values for the in-domain and zero
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- Install this package with with the `evaluation` extra:
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```
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pip install "chronos[evaluation] @ git+https://github.com/amazon-science/chronos-forecasting.git"
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pip install "chronos-forecasting[evaluation] @ git+https://github.com/amazon-science/chronos-forecasting.git"
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```
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- Run the evaluation script:
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```sh
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