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English(EN) DynaMiCS: Fine-Tuning LLMs with Performance Constraints Using Dynamic Mixtures

LoRA技术赋能大型AI模型高效微调

多篇文章讨论了大型语言模型的微调,特别关注LoRA(低秩适配)技术。LoRA通过仅训练一小部分参数来实现大型模型的有效适配,使其在性能较低的硬件上也能实现。该方法与需要大量计算资源的全量微调形成对比。文章还涉及了Adam等优化算法,这对于这些大型模型的实际训练至关重要,并探讨了机器学习模型的更广泛发展历程。 AI

影响 LoRA和高效微调技术正在加速大型AI模型在各种应用中的采用和定制,甚至可以在消费级硬件上实现。

排序理由 文章聚焦于机器学习模型微调的一种特定技术(LoRA),并讨论了优化算法,这属于AI/ML的研究范畴。

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LoRA技术赋能大型AI模型高效微调

报道来源 [7]

  1. Apple Machine Learning Research TIER_1 English(EN) ·

    DynaMiCS:使用动态混合物在性能约束下微调LLM

    Multi-domain fine-tuning of large language models requires improving performance on target domains while preserving performance on constrained domains, such as general knowledge, instruction following, or safety evaluations. Existing data mixing strategies rely on fixed heuristic…

  2. Medium — fine-tuning tag TIER_1 English(EN) · Mohsen Kheirandishfard ·

    LoRA:在小型机器上微调大模型——精度不打折

    <div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/@mohsen.kheirandishfard/lora-fine-tune-a-big-model-on-a-small-machine-without-losing-accuracy-ebeb98c9f01b?source=rss------fine_tuning-5"><img src="https://cdn-images-1.medium.com/max/1745/1*bO…

  3. Medium — fine-tuning tag TIER_1 English(EN) · Sanskruti Patro ·

    1%调优法则:微小改动如何改变你的机器学习模型

    <div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/@sanskruti.patro2005/the-1-tuning-rule-how-tiny-changes-can-transform-your-machine-learning-model-5a0753b44a8b?source=rss------fine_tuning-5"><img src="https://cdn-images-1.medium.com/max/1536/…

  4. Medium — fine-tuning tag TIER_1 English(EN) · Prajakta Bhondave ·

    机器学习模型的旅程与微调技术

    <div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/@prajaktabhondave/the-journey-of-a-machine-learning-model-fine-tuning-techniques-9c3be94e5b37?source=rss------fine_tuning-5"><img src="https://cdn-images-1.medium.com/max/1280/0*H8uY0ERyReJl5Xh…

  5. dev.to — LLM tag TIER_1 English(EN) · Shrijith Venkatramana ·

    Adam:让大型语言模型(LLM)得以实现的优化算法

    <p><em>Hello, I'm Shrijith Venkatramana. I'm building git-lrc, an AI code reviewer that runs on every commit. <a href="https://github.com/HexmosTech/git-lrc" rel="noopener noreferrer">Star Us</a> to help devs discover the project. Do give it a try and share your feedback for impr…

  6. dev.to — LLM tag TIER_1 English(EN) · Hiroki Kameyama ·

    微调 — 使用 LoRA 对模型进行领域专业化

    <h2> Introduction </h2> <p>In <a href="https://dev.to/hiroki-kameyama/mlops-llmops-cicd-pipelines-for-continuous-quality-assurance-46d1">Chapter 5 (MLOps)</a>, we built a CI/CD pipeline. This chapter explores a different approach: fine-tuning — training the model itself on your o…

  7. dev.to — LLM tag TIER_1 English(EN) · Devanshu Biswas ·

    LoRA:通过训练1%的模型来微调一个巨型模型

    <p>Fine-tuning a large model used to mean one painful thing: update every weight in it, keep a full copy per task, and pay for the GPUs to do it. A 7-billion-parameter model has 7 billion knobs. The Adam optimizer keeps two extra numbers per knob, so you're suddenly holding rough…