Practical Tips for Finetuning LLMs Using LoRA (Low-Rank Adaptation) - discu.eu

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Practical Tips for Finetuning LLMs Using LoRA (Low-Rank Adaptation) https://magazine.sebastianraschka.com/p/practical-tips-for-finetuning-llms 27 comments 19/11/2023

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[P] Practical Tips for Finetuning LLMs Using LoRA (Low-Rank Adaptation): Things I Learned From Hundreds of Experiments https://magazine.sebastianraschka.com/p/practical-tips-for-finetuning-llms 10 comments 19/11/2023 machinelearning

Linking pages

Linked pages

[2305.14314] QLoRA: Efficient Finetuning of Quantized LLMs https://arxiv.org/abs/2305.14314 129 comments
[2305.11206] LIMA: Less Is More for Alignment https://arxiv.org/abs/2305.11206 44 comments
Finetuning LLMs with LoRA and QLoRA: Insights from Hundreds of Experiments - Lightning AI https://lightning.ai/pages/community/lora-insights/ 39 comments
LLM Training: RLHF and Its Alternatives https://magazine.sebastianraschka.com/p/llm-training-rlhf-and-its-alternatives 14 comments
[2106.09685] LoRA: Low-Rank Adaptation of Large Language Models https://arxiv.org/abs/2106.09685 8 comments
[2305.14342] Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training https://arxiv.org/abs/2305.14342 8 comments
Ahead of AI #9: LLM Tuning & Dataset Perspectives https://magazine.sebastianraschka.com/p/ahead-of-ai-9-llm-tuning-and-dataset 4 comments
GitHub - tatsu-lab/stanford_alpaca https://github.com/tatsu-lab/stanford_alpaca 2 comments

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