PEFT/agents evals + MeMo memory + OpenClaw/Hermes
Key Questions
What PEFT techniques are used with Gemma 4?
Unsloth QLoRA enables efficient fine-tuning of Gemma 4 on consumer hardware, reinforcing viability for local setups.
How do Hermes and OpenClaw agents function?
Hermes/OpenClaw/ZeroClaw are self-evolving agents that leverage local models for iterative improvement and coding tasks.
Are there beginner resources for fine-tuning local models?
A fine-tuning primer for beginners has been added, along with Polish-language tutorials using Unsloth for models like Bielik 2.6.
Hermes/OpenClaw/ZeroClaw self-evolving agents; Unsloth QLoRA. Gemma 4 fine-tuning examples reinforce consumer hardware viability. New: Pi Coding Agent emerges as lightweight alternative for local coding agents; beginner tutorial for building local agents with Ollama+LangChain. Latest: Practical quant guide for 8B function-calling model on RTX 3060 (quantization for agentic planning); Polish-language fine-tuning tutorial for Bielik 2.6 with Unsloth; PyData talk on building agentic apps with SLMs, LangChain, and MCP. Today: Fine-tuning primer for beginners added.