챗봇 UI는 ChatGPT를 위한 사용자 인터페이스로, 그 기능과 사용자 경험을 향상시키기 위해 제작되었습니다.
챗봇 UI를 사용하려면 기존의 ChatGPT 시스템에 통합하기만 하면 됩니다. 이 UI는 챗봇과 상호작용하기 위한 직관적인 인터페이스를 제공합니다. 사용자는 메시지를 보내고 응답을 받으며 자연스러운 대화를 원활하게 진행할 수 있습니다.
더 많은 문의사항이 있으면 문의하기 페이지(https://twitter.com/mckaywrigley)를 방문하세요.
챗봇 UI 회사 이름: Takeoff AI .
챗봇 UI에 대해 자세히 알아보려면 회사 소개 페이지(https://github.com/mckaywrigley/chatbot-ui)를 방문하세요. .
챗봇 UI 로그인 링크: https://www.chatbotui.com/login
챗봇 UI 가입 링크: https://www.chatbotui.com/login
챗봇 UI Twitter 링크: https://twitter.com/mckaywrigley
챗봇 UI Github 링크: https://github.com/mckaywrigley/chatbot-ui
작성자: Emmett 님의 글 4월 14 2024
AI UI 메이커를 만들기 위한 최고의 14가지 팁을 배우세요. 디자인 스킬을 지금 단계로 높이세요!
소셜 리스닝
Data Extraction with Large Language Models
➡️ JSON Extraction Scripts and/or ADVANCED-inference Repo Access: https://trelis.com/enterprise-server-api-and-inference-guide/ ➡️ ADVANCED-fine-tuning Repo: https://trelis.com/advanced-fine-tuning-scripts/ ➡️ Trelis Function-calling Models: https://trelis.com/function-calling/ ➡️ One-click Fine-tuning & Inference Templates: https://github.com/TrelisResearch/one-click-llms/ ➡️ Trelis Newsletter: https://Trelis.Substack.com ➡️ Tip Jar and Discord: https://ko-fi.com/trelisresearch Affiliate Links (support the channel): - Vast AI - https://cloud.vast.ai/?ref_id=98762 - RunPod - https://tinyurl.com/4b6ecbbn Resources: - Slides: http://tinyurl.com/3m9ckm4s - One-click-llms: https://github.com/TrelisResearch/one-click-llms - Chat interfaces: chat.trelis.com or chatbotui.com Hat tip to Sagar Desai for his insights and help on this vid. Check out his blog on LLMs here: https://sdcodehub.github.io/ Chapters 0:00 Introduction to Data Extraction with Language Models 0:28 Overview of the Video 3:26 Challenges in Data Extraction 5:13 JSON Extraction and YAML Extraction 13:27 Practical Demonstration of Data Extraction Using Open Chat 31:44 Comparing GPT 4 and GPT 3.5 for data extraction 34:37 Comparing Performance of Different Models 40:34 Extracting Data from Long Contexts 51:53 Exploring the Cost of Different Data Extraction Approaches 55:43 Conclusion and Final Thoughts
Exploring Three Handy Chatbot Tools 🤖
In this video, I will introduce you to three chatbot tools that I find handy. The first tool is labs.perplexity.ai, which allows you to chat with Llama models of different sizes. The second tool is chatbotui.com, a replica of OpenAI's chatbot that lets you set temperature and system prompts for more control over responses. Lastly, I will show you llama.cpp, a browser-based tool with a user-friendly interface and customizable system prompts. Links: - Llama Chatbot: labs.perplexity.ai - Web UI for OpenAI API keys: chatbotui.com - Run Llama on your computer: https://github.com/TrelisResearch/llamacpp-install-basics/blob/main/instructions.md - Google Colab: https://colab.research.google.com/drive/1u8x41Jx8WWtI-nzHOgqTxkS3Q_lcjaSX 00:00 Introduction 01:03 Tool 1: labs.proplexity.ai 01:29 Tool 2: chatbotui.com 03:40 Tool 3: llama CCP 06:34 Bonus: Chatting in a Jupyter Notebook Check out also Trelis' notebooks for fine-tuning and function calling: # 1. ADVANCED Fine-tuning Notebook This advanced script provides improved performance when training with small datasets: - Includes a prompt loss-mask for improved performance when structured responses are required. - Includes a stop token after responses - allowing the model to provide a short reponse (e.g. a function call) and then stop. - Request access here: https://buy.stripe.com/5kA5l69K52Hxf3a006. €14.99 (or $16.49) per seat/user. Access will be provided within 24 hours of purchase. # 2. Function Calling Dataset - Commercial dataset allowing language models to be fine-tuned for function calling. Get access here: https://huggingface.co/datasets/Trelis/function_calling_extended. - Created using only human input or Apache 2 licensed datasets (no third party commercial licensing limitations)