- 使用 PyTorch 或 TensorFlow 等深度學習框架的經驗
- 熟悉大型語言模型及其應用程式
- 了解分散式計算概念
觀眾
- 機器學習工程師
- 雲 AI 專家
優化大型模型以進行微調對於使高級 AI 應用程式可行且具有成本效益至關重要。本課程重點介紹降低計算成本的策略，包括分散式訓練、模型量化和硬體優化，使參與者能夠高效地部署和微調大型模型。
這種由講師指導的現場培訓（在線或現場）面向希望掌握優化大型模型的技術，以便在實際場景中進行經濟高效的微調的高級專業人員。
在本次培訓結束時，參與者將能夠：
- 瞭解微調大型模型的挑戰。
- 將分散式訓練技術應用於大型模型。
- 利用模型量化和修剪提高效率。
- 優化微調任務的硬體利用率。
- 在生產環境中有效地部署微調的模型。
課程形式
- 互動講座和討論。
- 大量的練習和練習。
- 在即時實驗室環境中動手實施。
課程自定義選項
- 要申請本課程的定製培訓，請聯繫我們進行安排。
優化大型模型簡介
- 大型模型體系結構概述
- 微調大型模型的挑戰
- 成本效益優化的重要性
分散式訓練技術
- 數據和模型並行性簡介
- 分散式訓練框架：PyTorch 和 TensorFlow
- 跨多個 GPU 和節點擴展
模型量化和修剪
- 瞭解量化技術
- 應用修剪以減小模型大小
- 準確性和效率之間的權衡
硬體優化
- 為微調任務選擇合適的硬體
- 優化 GPU 和 TPU 利用率
- 對大型模型使用專用加速器
高效 Data Management
- 管理大型數據集的策略
- 性能的預處理和批處理
- 數據增強技術
部署優化的模型
- 部署微調模型的技術
- 監控和維護模型性能
- 優化模型部署的真實示例
高級優化技術
- 探索低秩適應 （LoRA）
- 使用適配器進行模組化微調
- 模型優化的未來趨勢
總結和後續步驟
United Arab Emirates - Optimizing Large Models for Cost-Effective Fine-Tuning
Qatar - Optimizing Large Models for Cost-Effective Fine-Tuning
Egypt - Optimizing Large Models for Cost-Effective Fine-Tuning
Saudi Arabia - Optimizing Large Models for Cost-Effective Fine-Tuning
South Africa - Optimizing Large Models for Cost-Effective Fine-Tuning
Brasil - Optimizing Large Models for Cost-Effective Fine-Tuning
Canada - Optimizing Large Models for Cost-Effective Fine-Tuning
中国 - Optimizing Large Models for Cost-Effective Fine-Tuning
香港 - Optimizing Large Models for Cost-Effective Fine-Tuning
澳門 - Optimizing Large Models for Cost-Effective Fine-Tuning
台灣 - Optimizing Large Models for Cost-Effective Fine-Tuning
USA - Optimizing Large Models for Cost-Effective Fine-Tuning
Österreich - Optimizing Large Models for Cost-Effective Fine-Tuning
Schweiz - Optimizing Large Models for Cost-Effective Fine-Tuning
Deutschland - Optimizing Large Models for Cost-Effective Fine-Tuning
Czech Republic - Optimizing Large Models for Cost-Effective Fine-Tuning
Denmark - Optimizing Large Models for Cost-Effective Fine-Tuning
Estonia - Optimizing Large Models for Cost-Effective Fine-Tuning
Finland - Optimizing Large Models for Cost-Effective Fine-Tuning
Greece - Optimizing Large Models for Cost-Effective Fine-Tuning
Magyarország - Optimizing Large Models for Cost-Effective Fine-Tuning
Ireland - Optimizing Large Models for Cost-Effective Fine-Tuning
Luxembourg - Optimizing Large Models for Cost-Effective Fine-Tuning
Latvia - Optimizing Large Models for Cost-Effective Fine-Tuning
España - Optimizing Large Models for Cost-Effective Fine-Tuning
Italia - Optimizing Large Models for Cost-Effective Fine-Tuning
Lithuania - Optimizing Large Models for Cost-Effective Fine-Tuning
Nederland - Optimizing Large Models for Cost-Effective Fine-Tuning
Norway - Optimizing Large Models for Cost-Effective Fine-Tuning
Portugal - Optimizing Large Models for Cost-Effective Fine-Tuning
România - Optimizing Large Models for Cost-Effective Fine-Tuning
Sverige - Optimizing Large Models for Cost-Effective Fine-Tuning
Türkiye - Optimizing Large Models for Cost-Effective Fine-Tuning
Malta - Optimizing Large Models for Cost-Effective Fine-Tuning
Belgique - Optimizing Large Models for Cost-Effective Fine-Tuning
France - Optimizing Large Models for Cost-Effective Fine-Tuning
日本 - Optimizing Large Models for Cost-Effective Fine-Tuning
Australia - Optimizing Large Models for Cost-Effective Fine-Tuning
Malaysia - Optimizing Large Models for Cost-Effective Fine-Tuning
New Zealand - Optimizing Large Models for Cost-Effective Fine-Tuning
Philippines - Optimizing Large Models for Cost-Effective Fine-Tuning
Singapore - Optimizing Large Models for Cost-Effective Fine-Tuning
Thailand - Optimizing Large Models for Cost-Effective Fine-Tuning
Vietnam - Optimizing Large Models for Cost-Effective Fine-Tuning
India - Optimizing Large Models for Cost-Effective Fine-Tuning
Argentina - Optimizing Large Models for Cost-Effective Fine-Tuning
Chile - Optimizing Large Models for Cost-Effective Fine-Tuning
Costa Rica - Optimizing Large Models for Cost-Effective Fine-Tuning
Ecuador - Optimizing Large Models for Cost-Effective Fine-Tuning
Guatemala - Optimizing Large Models for Cost-Effective Fine-Tuning
Colombia - Optimizing Large Models for Cost-Effective Fine-Tuning
México - Optimizing Large Models for Cost-Effective Fine-Tuning
Panama - Optimizing Large Models for Cost-Effective Fine-Tuning
Peru - Optimizing Large Models for Cost-Effective Fine-Tuning
Uruguay - Optimizing Large Models for Cost-Effective Fine-Tuning
Venezuela - Optimizing Large Models for Cost-Effective Fine-Tuning
Polska - Optimizing Large Models for Cost-Effective Fine-Tuning
United Kingdom - Optimizing Large Models for Cost-Effective Fine-Tuning
South Korea - Optimizing Large Models for Cost-Effective Fine-Tuning
Pakistan - Optimizing Large Models for Cost-Effective Fine-Tuning
Sri Lanka - Optimizing Large Models for Cost-Effective Fine-Tuning
Bulgaria - Optimizing Large Models for Cost-Effective Fine-Tuning
Bolivia - Optimizing Large Models for Cost-Effective Fine-Tuning
Indonesia - Optimizing Large Models for Cost-Effective Fine-Tuning
Kazakhstan - Optimizing Large Models for Cost-Effective Fine-Tuning
Moldova - Optimizing Large Models for Cost-Effective Fine-Tuning
Morocco - Optimizing Large Models for Cost-Effective Fine-Tuning
Tunisia - Optimizing Large Models for Cost-Effective Fine-Tuning
Kuwait - Optimizing Large Models for Cost-Effective Fine-Tuning
Oman - Optimizing Large Models for Cost-Effective Fine-Tuning
Slovakia - Optimizing Large Models for Cost-Effective Fine-Tuning
Kenya - Optimizing Large Models for Cost-Effective Fine-Tuning
Nigeria - Optimizing Large Models for Cost-Effective Fine-Tuning
Botswana - Optimizing Large Models for Cost-Effective Fine-Tuning
Slovenia - Optimizing Large Models for Cost-Effective Fine-Tuning
Croatia - Optimizing Large Models for Cost-Effective Fine-Tuning
Serbia - Optimizing Large Models for Cost-Effective Fine-Tuning
Bhutan - Optimizing Large Models for Cost-Effective Fine-Tuning
Nepal - Optimizing Large Models for Cost-Effective Fine-Tuning
Uzbekistan - Optimizing Large Models for Cost-Effective Fine-Tuning