[WIP] use felo tool (felo search from ddg-search mcp) and search web for all type of trainers (sfttrainer, dpotrainer etc) https://github.com/huggingface/trl/tree/main/trl/trainer https://github.com/unslothai/unsloth see all files in these and then implemen...

[Copilot]

• Research TRL trainers and Unsloth optimizations using felo search tool
• Analyze current llm-trainer codebase structure and capabilities
• Set up development environment with required dependencies
• Create trainers module with specialized trainer classes
• Implement SFTTrainer (Supervised Fine-Tuning)
• Implement DPOTrainer (Direct Preference Optimization)
• Implement PPOTrainer (Proximal Policy Optimization)
• Implement RewardTrainer for reward model training
• Create optimization module with Unsloth-style optimizations
• Implement LoRA/QLoRA support for parameter-efficient fine-tuning
• Add Flash Attention implementation for memory efficiency
• Implement gradient checkpointing and memory optimizations
• Add quantization support (4-bit, 8-bit)
• Create configuration classes for each trainer type
• Update main package exports and documentation
• Add example usage scripts
• Test implementations and ensure compatibility

Goal: Transform llm-trainer into a comprehensive training framework that supports multiple training paradigms (SFT, DPO, PPO, etc.) with Unsloth-style optimizations achieving 2-4x faster training and 80% less VRAM usage.

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