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v1.1.2
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Release 1.1.2
New Features
Reinforcement Fine-Tuning (RFT) Multiturn
Added RFT Multiturn data transformer and validator.
Added support for session restoration using dump() and load().
Enabled custom starter kit path via starter_kit_path to use custom environments.
Deprecated start_training_environment() and start_evaluation_environment() in favor of start_environment().
Added a feature to detect duplicate environments running on same stack and infrastructure.
Reinforcement Fine-Tuning (RFT) Singleturn
Introduced RFT Lambda verification via the validation_config parameter in NovaModelCustomizer.
Job Caching
Added enable_job_caching to NovaModelCustomizer to save job results to disk and reuse them on subsequent calls with matching parameters.
Enhancements
Validation for SageMaker Inference (SMI) Configs
Added validation for context length and concurrency settings based on model and instance type when deploying to SMI endpoints.
Bug Fixes
Fixed validation logic for save_steps for RFT multiturn to accept integer values.
Removed pinned version constraint for numpy (numpy<=2.2.6) to resolve dependency conflicts.
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