*Issue #, if available:*
*Description of changes:*
- Refactor the notebook to cover real-time inference (CPU & GPU),
serverless inference and batch prediction options for Chronos-2 on
SageMaker
- Update README
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*Issue #, if available:*
*Description of changes:*
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*Issue #, if available:*
*Description of changes:* Adds support for LoRA fine-tuning.
- [x] Move peft/pandas dependency to an extra
- [x] Add tests for LoRA
- [x] Update notebook with LoRA info
- [x] Enable automatic recognition and loading of LoRA adapters
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*Issue #, if available:*
*Description of changes:* Lower learning rates generally appear to be
working better. This is probably because we are doing full fine-tuning
of a model with 120M params.
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*Issue #, if available:*
*Description of changes:*
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---------
Co-authored-by: Oleksandr Shchur <oleks.shchur@gmail.com>
*Issue #, if available:*
*Description of changes:*
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choice.
*Issue #, if available:*
*Description of changes:*
- Add notebook showcasing how Chronos-2 can be deployed using Amazon
SageMaker
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choice.
*Issue #, if available:*
*Description of changes:*
- Move the SageMaker deployment notebook to a new path to check that the
GitHub redirect feature works.
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*Issue #, if available:*
*Description of changes:*
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*Issue #, if available:*
*Description of changes:*
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copy, and redistribute this contribution, under the terms of your
choice.
*Issue #, if available:*
*Description of changes:* Update README for Chronos-2
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copy, and redistribute this contribution, under the terms of your
choice.
---------
Co-authored-by: Oleksandr Shchur <oleks.shchur@gmail.com>
*Issue #, if available:*
*Description of changes:*
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copy, and redistribute this contribution, under the terms of your
choice.
*Issue #, if available:*
*Description of changes:*
- Add pointers to fev and JumpStart notebook in the README
- Add notebook describing how to deploy Chronos with SageMaker JumpStart
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copy, and redistribute this contribution, under the terms of your
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