https://www.youtube.com/watch?v=eTieetk2dSw 历史提问 https://app.sli.do/event/erFLUz3s8yWhRZkFAkSx9b/live/questions 知识 校园学习 人工智能 ChatGPT InstructionTunedLLM 微调 吴恩达 LLM GPT中英字幕课程资源 发消息 求课看置顶。定制双语字幕私微gpt_sub,GPT-3.5,0.2R每分钟,gpt-4o,0.5R一...
While designing each "leaf" of my LLM workflow graph, or LLM-native architecture, I follow theLLM Triangle Principles³ to determine where and when to cut the branches, split them, or thicken the roots (by using prompt engineering techniques) and squeeze more of the lemon. 在设计 LLM 工作...
Then, we will code a small GPT-like LLM, including its data input pipeline, core architecture components, and pretraining code ourselves. After understanding how everything fits together and how to pretrain an LLM, we will learn how to load pretrained weights and finetune LLMs using open-...
Coming soon... Pages 12 Home 0. API glossary 0. Design intent of PanML 1. Quick start guide 2. Prompt chain engineering 3. Fine tuning your LLM 4. Prompted code generation 5. Generative model analysis 6. Building a LLM application 7. Retrieve similar documents using vector...
The development and release of ChatGPT and other state-of-the-art large language models (LLMs) has renewed interest in the concept of AI agents, a term that evokes a range of assumptions about their potential as applications to independently automate many tasks along with the risks they presen...
In part 1 of a new blog series, we show how to build a search engine in 100 lines using LLM embeddings and a vector database.
As mentioned one of the solutions to the hallucinations problem is providing the proper context to the input prompt to limit the LLM's freedom to hallucinate. However, on the other hand, LLMs have a limit on the number of words that can be used. One possible solution for this problem is...
Boba is a web application that mediates an interaction between a human user and a Large-Language Model, currently GPT 3.5. A simple web front-end to an LLM just offers the ability for the user to converse with the LLM. This is helpful, but means the user needs to learn how to effectiv...
Lanarky provides a powerful abstraction layer to allow developers to build simple LLM microservices in just a few lines of code. Here's an example to build a simple microservice that uses OpenAI'sChatCompletionservice: fromlanarkyimportLanarkyfromlanarky.adapters.openai.resourcesimportChatCompletionReso...
The growing number of parameter-efficient adaptations of a base large language model (LLM) calls for studying whether we can reuse such trained adapters to improve performance for new tasks. We study how to best build a library of adapters given multi-task data and devise...