ml-ops
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6 Open-Source Libraries to FineTune LLMs 1. Unsloth GitHub: https://lnkd.in/gQvPWVFb → Fastest way to fine-tune LLMs locally → Optimized for low VRAM (even laptops) → Plug-and-play with Hugging Face models 2. Axolotl GitHub: https://lnkd.in/g34kuExT → Flexible LLM fine-tuning configs → Supports LoRA, QLoRA, multi-GPU → Great for custom training pipelines 3. TRL (Transformer Reinforcement Learning) GitHub: https://lnkd.in/gnxQBVAc → RLHF, DPO, PPO for LLM alignment → Built on Hugging Face ecosystem → Essential for post-training optimization 4. DeepSpeed GitHub: https://lnkd.in/gEdkFWdB → Train massive models efficiently → Memory + speed optimization → Industry standard for scaling 5. LLaMA-Factory GitHub: https://lnkd.in/gbdWBDsD → All-in-one fine-tuning UI + CLI → Supports multiple models (LLaMA, Qwen, etc.) → Beginner-friendly + powerful 6. PEFT GitHub: https://lnkd.in/g7fBjh2E → Fine-tune with minimal compute → LoRA, adapters, prefix tuning → Best for cost-efficient training Save this for future use. | 46 comments on LinkedIn
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