AI/ML

AI/ML

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Non-engineers guide: Train a LLaMA 2 chatbot
Non-engineers guide: Train a LLaMA 2 chatbot
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
·huggingface.co·
Non-engineers guide: Train a LLaMA 2 chatbot
Web Scraping using ChatGPT - Complete Guide with Examples | ProxiesAPI
Web Scraping using ChatGPT - Complete Guide with Examples | ProxiesAPI
Web scraping using ChatGPT: extract data from websites using code. ChatGPT is a powerful tool for web scraping. Techniques include using Selenium and Beautiful Soup. Get started now!
·proxiesapi.com·
Web Scraping using ChatGPT - Complete Guide with Examples | ProxiesAPI
What is LoRA? Low-Rank Adaptation for finetuning LLMs EXPLAINED
What is LoRA? Low-Rank Adaptation for finetuning LLMs EXPLAINED
How does LoRA work? Low-Rank Adaptation for Parameter-Efficient LLM Finetuning explained. Works for any other neural network as well, not just for LLMs. 📜 „Lora: Low-rank adaptation of large language models“ Hu, E.J., Shen, Y., Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L. and Chen, W., 2021. https://arxiv.org/abs/2106.09685 📚 https://sebastianraschka.com/blog/2023/llm-finetuning-lora.html 📽️ LoRA implementation: https://youtu.be/iYr1xZn26R8 Thanks to our Patrons who support us in Tier 2, 3, 4: 🙏 Dres. Trost GbR, Siltax, Vignesh Valliappan, Mutual Information, Kshitij Outline: 00:00 LoRA explained 00:59 Why finetuning LLMs is costly 01:44 How LoRA works 03:45 Low-rank adaptation 06:14 LoRA vs other approaches ▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀ 🔥 Optionally, pay us a coffee to help with our Coffee Bean production! ☕ Patreon: https://www.patreon.com/AICoffeeBreak Ko-fi: https://ko-fi.com/aicoffeebreak ▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀ 🔗 Links: AICoffeeBreakQuiz: https://www.youtube.com/c/AICoffeeBreak/community Twitter: https://twitter.com/AICoffeeBreak Reddit: https://www.reddit.com/r/AICoffeeBreak/ YouTube: https://www.youtube.com/AICoffeeBreak #AICoffeeBreak #MsCoffeeBean #MachineLearning #AI #research​ Music 🎵 : Meadows - Ramzoid Video editing: Nils Trost
·youtube.com·
What is LoRA? Low-Rank Adaptation for finetuning LLMs EXPLAINED
Causality for Machine Learning
Causality for Machine Learning
An online research report on causality for machine learning by Cloudera Fast Forward.
·ff13.fastforwardlabs.com·
Causality for Machine Learning
Rethinking the Luddites in the Age of A.I.
Rethinking the Luddites in the Age of A.I.
Brian Merchant’s new book, “Blood in the Machine,” argues that Luddism stood not against technology per se but for the rights of workers in the face of automation.
·newyorker.com·
Rethinking the Luddites in the Age of A.I.
Student Use Cases for AI
Student Use Cases for AI
Dive into this series of 4 student use cases for AI to discover how generative AI tools like ChatGPT can be used as a feedback generator, tutor, team coach, and learner. Get sample prompts and shareable guidelines to help students use AI tools effectively.
·hbsp.harvard.edu·
Student Use Cases for AI
Commonplace Bot Basic Workflow
Commonplace Bot Basic Workflow
https://github.com/bramses/commonplace-bot/tree/main----------WEEKLY NEWSLETTER: https://www.bramadams.dev/STENOGRAPHY: https://stenography.dev/GITHUB: https...
·youtube.com·
Commonplace Bot Basic Workflow
A Hackers' Guide to Language Models
A Hackers' Guide to Language Models
For the notebook used in this talk, see https://github.com/fastai/lm-hackers . This is an extended version of the keynote given at posit::conf(2023).
·youtube.com·
A Hackers' Guide to Language Models
mohamed-chs/chatgpt-history-export-to-md: A Python script to effortlessly extract and format your ChatGPT conversations data export from JSON files to well-structured markdown files, with YAML metadata headers. And it all happens locally !
mohamed-chs/chatgpt-history-export-to-md: A Python script to effortlessly extract and format your ChatGPT conversations data export from JSON files to well-structured markdown files, with YAML metadata headers. And it all happens locally !
·github.com·
mohamed-chs/chatgpt-history-export-to-md: A Python script to effortlessly extract and format your ChatGPT conversations data export from JSON files to well-structured markdown files, with YAML metadata headers. And it all happens locally !
Chat gpt20
Chat gpt20
·www-cs-faculty.stanford.edu·
Chat gpt20
Chatbots with RAG: LangChain Full Walkthrough
Chatbots with RAG: LangChain Full Walkthrough
In this video, we work through building a chatbot using Retrieval Augmented Generation (RAG) from start to finish. We use OpenAI's gpt-3.5-turbo Large Language Model (LLM) as the "engine", we implement it with LangChain's ChatOpenAI class, use OpenAI's text-embedding-ada-002 for embedding, and the Pinecone vector database as our knowledge base. 📌 Code: https://github.com/pinecone-io/examples/blob/master/learn/generation/langchain/rag-chatbot.ipynb 🌲 Subscribe for Latest Articles and Videos: https://www.pinecone.io/newsletter-signup/ 👋🏼 AI Consulting: https://aurelio.ai 👾 Discord: https://discord.gg/c5QtDB9RAP Twitter: https://twitter.com/jamescalam LinkedIn: https://www.linkedin.com/in/jamescalam/ 00:00 Chatbots with RAG 00:59 RAG Pipeline 02:35 Hallucinations in LLMs 04:08 LangChain ChatOpenAI Chatbot 09:11 Reducing LLM Hallucinations 13:37 Adding Context to Prompts 17:47 Building the Vector Database 25:14 Adding RAG to Chatbot 28:52 Testing the RAG Chatbot 32:56 Important Notes when using RAG #artificialintelligence #nlp #ai #langchain #openai #vectordb
·youtube.com·
Chatbots with RAG: LangChain Full Walkthrough
Onboard AI
Onboard AI

Navigate unfamiliar codebases using AI. Step 1: Clone a GitHub repository Step 2: Ask questions to find your way around

·getonboard.dev·
Onboard AI