CachedSpladeLoss

This release focuses on correctness and performance, rebuilding gradient-cached losses on a shared engine for faster training and fixing several gradient bugs. It also significantly improves inference speed when using `model.compile()`.

This minor release enhances contrastive learning with new loss formulations and hardness weighting for MultipleNegativesRankingLoss, and introduces memory-efficient CachedSpladeLoss and GlobalOrthogonalRegularizationLoss. Bug fixes include addressing issues with GroupByLabelBatchSampler.