1 day agoLLM Training: In-Context LearningThe most basic and simple model training method is just like having a chat. At first, I didn’t think of it as “training,” but after using ChatGPT and Bard many times, I found that as long as you give the model a certain context and keep the historical records within…AI3 min readAI3 min read
5 days agoExperience with the LangChain App TemplateCreate wine price Q&A with the LangChain App Template We will utilize LangChain’s template to create a basic Q&A application, and utilize LLM to obtain price references for wine. Install LangChain CLI pip install -U langchain-cli OpenAI Key To use OpenAI by default, global setup is required. export OPENAI_API_KEY App creation In the…Langchain8 min readLangchain8 min read
6 days agoHow to Use OpenAI Assistants (API)Explore various approaches to using OpenAI Assistants with this guide. Use this article to learn about the different ways to utilize assistants through the API. Start In November 2023, OpenAI launched the API for Assistants. This is a bot(more than a bot) function hosted by OpenAI, where we only need to…AI11 min readAI11 min read
Nov 15Experimentation: LLM, LangChain Agent, Computer VisionConsider utilizing the Large Language Model(LLM) for automating annotation tasks, or for performing automatic object detection in Computer Vision, using the Agent (function in OpenAI) within LangChain. In other words, what we’re doing here is object detection without any human intervention. All we do is upload an image, then use…Large Language Models7 min readLarge Language Models7 min read
Sep 14Chat with your PDF （Streamlit Demo)Utilize the flow of the chatting with your own documents to interact with my PDF. Recently, many people have been discussing the use of LLMs, which can be basically divided into: Fine-tuning (Training pretrained model, Transfer learning, etc.) Applications based on LLMs, especially the very popular LangChain. This time, I…Artificial Intelligence4 min readArtificial Intelligence4 min read
Aug 24LLM fine-tuning step: TokenizingTokenization is a crucial phase in fine-tuning the LLM, requiring us to: Encode the input, which is typically a form of guiding text, such as a question. Decode the output, usually it’s a courteous response after the “generate()” method has been invoked. What is kind Tokenizing In simple terms, it means using a dictionary…Large Language Models2 min readLarge Language Models2 min read
Jul 31LLM applicationsMake LLMs prompting, and fine-tuning useful, efficient, and valid.Generative Model2 min readGenerative Model2 min read
Jul 22Fine-tuning LLMsTasks to finetune Before Fine-tuning (base or pretrained model)AI6 min readAI6 min read
Jul 16Mouse interactive prompt engineeringOne new method based on Segment(ation) Anything SAM Start Continuing the discussion on prompt engineering from last time, let’s talk about fast implementation for object segmentation in Computer Vision. This method was quite difficult before the emergence of SAM, even requiring separate training of image segmentation models for different targets. …AI4 min readAI4 min read
Jul 10AI new trend, prompt engineeringUse AI model to produce the outcome, better outcome, and best outcome Introduction In the past few days, I have already created two small tools using ChatGPT. AI in terminal Build a tiny bash to let the terminal support GPTteetracker.medium.com AI in Chrome Extension Development: Create a Chrome extension for English syntax and grammar check Recently, I suddenly became interested in packaging AI APIs. When I think about it, after a long period of model…teetracker.medium.comComputer Vision3 min readComputer Vision3 min read
