Fix OutOfMemoryError

✅ Solution

OutOfMemoryError typically arises when the model and training data exceed available GPU memory. Reduce batch size, use gradient accumulation, enable CPU offloading via `unsloth.utils.force_low_cpu_mem` if possible, or switch to a smaller model to decrease memory footprint and prevent the error. Consider upgrading your GPU or using distributed training across multiple GPUs if the problem persists.