在 Hugging Face 中微調 Gemma 模型
Original: Fine-Tuning Gemma Models in Hugging Face
After Google released the Gemma family of open-source models (including 2B and 7B parameter versions), Hugging Face promptly published this…
本指南介紹如何在 Hugging Face 生態系中微調 Google 的 Gemma 開源模型（2B 與 7B）。文章詳細說明了如何利用 PEFT（參數高效微調）技術，特別是 QLoRA（4-bit 量化微調），在消費級 GPU 上進行訓練。透過結合 transformers、peft 與 trl（SFTTrainer）等套件，開發者可以輕鬆載入模型、設定 LoRA 參數、格式化數據集，並將微調後的權重上傳至 Hugging Face Hub，是實作 Gemma 微調的必讀教學。
After Google released the Gemma family of open-source models (including 2B and 7B parameter versions), Hugging Face promptly published this practical fine-tuning guide, teaching developers how to perform customized training on Gemma using parameter-efficient fine-tuning (PEFT) techniques.
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