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To scale to very large model, we need to enable model parallelization and FSDP in Fortuna. We can do so by exploiting JAX sharding functionalities. In this PR, we plan to make training and fine-tuning methods in Fortuna working with shardings. The user will determine how many GPUs to allocate for each type of parallelization (data, FSD and model parallelization) and some simple model partitioning rules. Fortuna will do the rest.

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@gianlucadetommaso gianlucadetommaso marked this pull request as draft July 2, 2023 21:34
- create partition manager object
- make MAP compatible
- migrate to Orbax checkpointing
- refactor predictive
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