LoRA fine-tuning

SeekrFlow now supports low-rank adaptation (LoRA) support for parameter-efficient fine-tuning. LoRA trains small adapter layers while keeping the base model frozen, enabling faster training cycles and reduced computational costs compared to full fine-tuning.

Capabilities:

• Fine-tune models using LoRA with SFT and GRPO workflows
• Lower GPU memory requirements enable fine-tuning of larger models
• Reduced risk of catastrophic forgetting
• Configure via lora_config parameter in TrainingConfig (includes rank, alpha, and advanced fields)

User interface parity with Seekr-managed instance

Self-hosted instances now include all features and improvements released to Seekr-managed instances through September 2025. This release brings self-hosted deployments to feature parity with the managed interface, including SeekrFlow Explainability, Agent Observability Platform, Docstring Validation, AI Ready Data Engine quality enhancements, and SeekrFlow Helm Chart v2.0.