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Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
Last updated 29 days ago
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2.6.0EarlyStopping callback (#21188)ThroughputMonitor (#20236)EMAWeightAveraging callback that wraps Lightning's WeightAveraging class (#21260)weights_only argument for Trainer.{fit,validate,test,predict} and let torch handle default value (#21072)RichProgressBar and RichModelSummary if the rich package is available. Fallback to TQDMProgressBar and ModelSummary otherwise (#20896)max_trials is reached in Tuner.scale_batch_size (#21187)LightningCLI could not be initialized with trainer_default containing callbacks (#21192)ModelPruning is applied with lottery ticket hypothesis (#21191)save_last='link' and save_top_k=-1 (#21186)last.ckpt being created and not linked to another checkpoint (#21244)BackboneFinetuning from being used together with LearningRateFinder (#21224)ModelPruning sparsity logging bug that caused incorrect sparsity percentages (#21223)LightningCLI loading of hyperparameters from ckpt_path failing for subclass model mode (#21246)__init__ method (#21227)ThroughputMonitor calculated training time (#21291)DDPStrategy(static_graph=True) (#21251)Full commit list: 2.5.0 -> 2.6.0
We thank all folks who submitted issues, features, fixes and doc changes. It's the only way we can collectively make Lightning :zap: better for everyone, nice job!
In particular, we would like to thank the authors of the pull-requests above