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Wuyuhang11/Tutorialcamp3 Branches 0 Tags Code This branch is 128 commits behind InternLM/Tutorial:camp3.Folders and filesLatest commit vansin Update README.md 66b9b6d· Jul 14, 2024 History162 Commits configs update Jun 3, 2024 data Merge pull request InternLM#898 from coffeebean6/camp3...
5. Tutorial 面向开发者的 LLM 入门课程: 地址:github.com/datawhalechi 简介:一个中文版的大模型入门教程,围绕吴恩达老师的大模型系列课程展开,主要包括:吴恩达《ChatGPT Prompt Engineering for Developers》课程中文版,吴恩达《Building Systems with the ChatGPT API》课程中文版,吴恩达《LangChain for LLM Applicatio...
○ 地址:https://github.com/imClumsyPanda/langchain-ChatGLM ○ 简介:基于本地知识库的 ChatGLM 等大语言模型应用实现 2.3 外部挂件应用 ● wenda: ○ 地址:https://github.com/wenda-LLM/wenda ○ 简介:一个LLM调用平台。为小模型外挂知识库查找和设计自动执行动作,实现不亚于于大模型的生成能力。 ● Jit...
[7]https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/langchain [8]https://github.com/intel-analytics/bigdl-llm-tutorial [9]https://github.com/openai/whisper [10]https://huggingface.co/meta-llama/Llama-2-7b-chat-hf [11]https://github.com/langchain-ai/langchain [12...
链接：https://github.com/openreasoner/openr/blob/main/reports/Tutorial-LLM-Reasoning-Wang.pdf o1 的训练使用了强化学习技术，通过显式地嵌入一个原生「思维链」（NCoT）过程，可出色地完成复杂的推理任务。也就是说，o1 在生成响应之前可通过一步步地推理实现「深度思考」。从 OpenAI 发布的数据看，相比于...
gitclone--depth 1 https://github.com/rasbt/LLMs-from-scratch.git (If you downloaded the code bundle from the Manning website, please consider visiting the official code repository on GitHub athttps://github.com/rasbt/LLMs-from-scratchfor the latest updates.) ...
more information about building reliable, scalable pieces for the API agent for production, check out theAI Chatbot with Retrieval-Augmented Generation Workflow. If you’re looking to experiment with a production-grade RAG pipeline for your LLM application, visitNVIDIA/GenerativeAIExampleson GitHub. ...
我们来看看一个简单的 Transformer 模型,就是比较早出现的 Kyubyong 实现的 Transformer 模型:https://github.com/Kyubyong/transformer/tree/master/tf1.2_legacy 第14 节· 先训练和测试一下 Kyubyong Transformer 下载一个「德语-英语翻译」的数据集:https://drive.google.com/uc?id=1l5y6Giag9aRPwGtuZHswh3w...
Tutorial: Build a question-answering LLM agent For this tutorial, you build a question-answering (QA) agent that can help you talk to your data. To show that a fairly simple agent can tackle fairly hard challenges, you build an agent that can mine information from earnings calls. You can...