SakanaAI/self-adaptive-llms

Hypernetworks that adapt LLMs for specific benchmark tasks using only textual task description as the input

Go ahead and axolotl questions

[COLM 2024] LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition

Turn expensive prompts into cheap fine-tuned models

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

Open Source LLM toolkit to build trustworthy LLM applications. TigerArmor (AI safety), TigerRAG (embedding, RAG), TigerTune (fine-tuning)

Use PEFT or Full-parameter to CPT/SFT/DPO/GRPO 600+ LLMs (Qwen3.8, DeepSeek-V4, GLM-5.1, InternLM3, Llama4, ...) and 300+ MLLMs (Qwen3-VL, Qwen3-Omni, InternVL3.5, Ovis2.5, GLM5.3, Gemma4, Llava, Phi4, ...) (AAAI 2025).

Self-Adapting Language Models

Production focused Self-harnessed LM runtime (RLM) that allows the LM to call its sub-lm with DSPy signatures. Define your inputs, outputs, and tools — the model handles its own control flow. Get fully interpretable trajectories and performance that scales directly with model improvements. Without context rot.