transformers

797860c6 - feat: add flexible Liger Kernel configuration to TrainingArguments (#38911)

feat: add flexible Liger Kernel configuration to TrainingArguments (#38911) * feat: add flexible Liger Kernel configuration to TrainingArguments Add support for granular Liger Kernel configuration through a new `liger_kernel_config` parameter in TrainingArguments. This allows users to selectively enable/disable specific kernels (rope, swiglu, cross_entropy, etc.) instead of the current approach that rely on default configuration. Features: - Add `liger_kernel_config` dict parameter to TrainingArguments - Support selective kernel application for all supported models - Maintain full backward compatibility with existing `use_liger_kernel` flag Example usage: ```python TrainingArguments( use_liger_kernel=True, liger_kernel_config={ "rope": True, "swiglu": True, "cross_entropy": False, "fused_linear_cross_entropy": True } ) Closes #38905 * Address comments and update Liger section in Trainer docs