Technical Overview From LLaMA1 to LLaMA3.3 CloseMoreName clearedScan to Appreciate the Author on WeChatLike the AuthorOther AmountArticlesNo articlesLike the AuthorOther Amount¥Minimum Appreciation ¥0OKBackOther AmountMoreAppreciation Amount¥Minimum Appreciation ¥01234567890. , January 14, 2025 01:00 , ,
Click the card below to follow the “LiteAI” public account This article will introduce our work on efficiently extending the context length of large models with low resources:LongQLoRA. It will involve knowledge related to Position Interpolation and QLoRA, and we recommend combining it with previous articles to help understand this work: Illustration of RoPE Rotational … Read more
## Install Ollama Select the appropriate installation method based on your operating system, taking Linux CentOS as an example. Use the command `curl -fsSL https://ollama.com/install.sh | sh` to install (requires sudo privileges). After installation, you can verify if it was successful by running `ollama –version`. ### Start Ollama After successful installation, start the Ollama service … Read more
Background: Attempting to build search Agents based on a local Agent framework. Reference Website: https://docs.phidata.com/tools/website Basic Environment: Command line tools (Linux/Mac), python3 (set up an independent conda environment). Basic LLM: Download and install from the Ollama official website (if you have a ChatGPT membership, you can also use ChatGPT). AI Agent Framework: This time we … Read more
Follow the official account above to reply:Course Resources can be obtained from this course There is a course on Tang Guoliang Llama model architecture from theory to practice Tang Guoliang Llama model architecture from theory to practice Tang Guoliang Llama Model Architecture: From Theory to Practice In today’s era of rapid advancement in artificial intelligence, … Read more
Comprehensive Guide to LLaMA Architecture Technology 🧠G-MQA optimization attention mechanism, reducing overhead and improving efficiency, suitable for large models. 🔍RMSNorm replaces LayerNorm, reducing computation and enhancing stability, widely applied. 🌐RoPE improves positional encoding, integrating information to solve problems, aiding model understanding. ⚡SwiGLU combines functional advantages, enhancing performance and efficiency, used in complex scenarios. CloseMoreName clearedScan … Read more
Are you still troubled by the mixed quality and poor performance of domestic AI? Then let’s take a look at Dev Cat AI (3in1)! This is an integrated AI assistant that combines GPT-4, Claude3, and Gemini. It covers all models of these three AI tools. Including GPT-4o and Gemini flash Now you can own them … Read more
Are you still troubled by the uneven quality and poor performance of AI in China? Then let’s take a look at Dev Cat AI (3in1). This is an integrated AI assistant that combines GPT-4, Claude3, and Gemini. It covers all models of the three AI tools. Including GPT-4o and Gemini flash Now you can own … Read more
This article has several interesting points: 1. Visualization using Streamlit. 2. Calculating rolling averages and momentum indicators to understand market trends. 3. Using Llama 3 to interpret the data. First, install and import the following packages: import yfinance as yf import pandas as pd import schedule import time import ollama from datetime import datetime, timedelta … Read more
Click below 👇“AI Knowledge Exchange”Follow the official account Ollama is an open-source framework designed for the convenient deployment and operation of large language models (LLMs) on local machines. Its core feature is to simplify usage and provide an efficient technical architecture, allowing developers to easily access and use powerful AI language models. Ollama supports local … Read more