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Oct 27 • General discussion
🛟 The Ultimate Guide to Fine-Tuning LLMs
*To whom it may concern...
A 115-page guide covers everything you need to fine-tune LLMs, from fundamentals to advanced techniques.
What's covered:
- Task- and domain-specific fine-tuning
- Parameter-efficient methods: PEFT, LoRA, QLoRA, DoRA, HFT
- Expert-based architectures: MoE, Lamini Memory Tuning, MoA
- Alignment and optimization: PPO, DPO
- Model simplification: Pruning
If you’re serious about mastering LLM fine-tuning, this is one of the most comprehensive open resources available.
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🛟 The Ultimate Guide to Fine-Tuning LLMs
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