What is vector search? - Algolia Blog | Algolia
Learn AI
How to Build a Local Chatbot with Llama2 and LangChain | by Aashish Nair | in Towards Data Science - Freedium
Overview and Implementation with Python
Mozilla-Ocho/llamafile: Distribute and run LLMs with a single file.
Distribute and run LLMs with a single file. Contribute to Mozilla-Ocho/llamafile development by creating an account on GitHub.
RAG with Llama-Index: Vector Stores
In this third video of our series on Llama-index, we will explore how to use different vector stores in llama-index while building RAG applications. We will ...
Building and Evaluating Advanced RAG Applications - DeepLearning.AI
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Prompt Engineering for Developers: How AI Can Help With Architecture Decisions
Learn effective prompt engineering techniques for Large Language Models (LLMs) based on generative AI, like ChatGPT, to facilitate software architecture decisions.
What is a Vector Database? | Pinecone
The nature of vector embeddings require new methods of storage and retrieval. We need a new kind of database.
All You Need to Know about Vector Databases and How to Use Them to Augment Your LLM Apps | by Dominik Polzer | in Towards Data Science - Freedium
A Step-by-Step Guide to Discover and Harness the Power of Vector Databases
Prompt Engineering Roadmap - roadmap.sh
Step by step guide to learn Prompt Engineering. We also have resources and short descriptions attached to the roadmap items so you can get everything you want to learn in one place.
Public: Learning Map to become a Data & AI Scientist at Careem
Sheet1
Step,Competence,Substep,How to grow,Expected Time
1,Math,Linear Algebra, Calculus, Mathematical Analysis,a href="https://www.coursera.org/specializations/mathematics-machine-learning#courses"https://www.coursera.org/specializations/mathematics-machine-learning#courses/a,1 month
Differ...
1706 - Attention is All You Need
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Deep Learning
The Illustrated Transformer
Discussions:
Hacker News (65 points, 4 comments), Reddit r/MachineLearning (29 points, 3 comments)
Translations: Arabic, Chinese (Simplified) 1, Chinese (Simplified) 2, French 1, French 2, Italian, Japanese, Korean, Persian, Russian, Spanish 1, Spanish 2, Vietnamese
Watch: MIT’s Deep Learning State of the Art lecture referencing this post
In the previous post, we looked at Attention – a ubiquitous method in modern deep learning models. Attention is a concept that helped improve the performance of neural machine translation applications. In this post, we will look at The Transformer – a model that uses attention to boost the speed with which these models can be trained. The Transformer outperforms the Google Neural Machine Translation model in specific tasks. The biggest benefit, however, comes from how The Transformer lends itself to parallelization. It is in fact Google Cloud’s recommendation to use The Transformer as a reference model to use their Cloud TPU offering. So let’s try to break the model apart and look at how it functions.
The Transformer was proposed in the paper Attention is All You Need. A TensorFlow implementation of it is available as a part of the Tensor2Tensor package. Harvard’s NLP group created a guide annotating the paper with PyTorch implementation. In this post, we will attempt to oversimplify things a bit and introduce the concepts one by one to hopefully make it easier to understand to people without in-depth knowledge of the subject matter.
2020 Update: I’ve created a “Narrated Transformer” video which is a gentler approach to the topic:
A High-Level Look
Let’s begin by looking at the model as a single black box. In a machine translation application, it would take a sentence in one language, and output its translation in another.
Embeddings - LlamaIndex 🦙 0.9.7
ivanfioravanti/chatbot-ollama: Chatbot Ollama is an open source chat UI for Ollama.
Chatbot Ollama is an open source chat UI for Ollama.
Vector Databases and How to Pick the Right One | by Ketan | in FabricHQ - Freedium
In the 1960s when the need for efficient data management arose with the growing volume of...
What is a Vector Database? - Zilliz Vector database blog
A vector database is a dedicated solution for storing, indexing and searching across a massive dataset of unstructured data used in AI applications.
What is a Vector Database? (2021) | Hacker News
Python Vector Databases and Vector Indexes: Architecting LLM Apps - KDnuggets
Vector databases enable fast similarity search and scale across data points. For LLM apps, vector indexes can simplify architecture over full vector databases by attaching vectors to existing storage. Choosing indexes vs databases depends on specialized needs, existing infrastructure, and broader enterprise requirements.
Implementing Vector Database for AI
What are vector databasesWhy are vector databases important to AICore concepts of a vector databaseFactors to consider when choosing a vector databasePopular Vector Databases for your considerationStep by Step guide to implementing a Vector databaseStep 1 : Installing MilvusStep 2: Creating a Milvus ClientStep 3 : Create a collectionStep 4: Inserting data
Introducing Vector-Storage: A Lightweight Vector Database for the Browser | by Nitai Aharoni 🎾 - Freedium
In the world of natural language processing (NLP), vector embeddings have become a powerful tool...
Storage Limitations: The browser's local storage has a size limit of approximately 5MB, which may limit the number of document vectors that can be stored. Vector Storage addresses this by implementing an LRU mechanism to manage storage size.
Top 10 best vector databases and libraries
A vector database is a type of database that stores data as high-dimensional vectors, which are mathematical representations of features or attributes.
Elasticsearch
Encoding data with Transformers | by Michelangiolo Mazzeschi | in Towards Data Science - Freedium
How to use transformer-based technology to perform data encoding
Leveraging LLMs in your Obsidian Notes · Ollama Blog
This post walks through how you could incorporate a local LLM using Ollama in Obsidian, or potentially any note taking tool.
Ollama
Get up and running with large language models, locally.
Text to Speech & AI Voice Generator
Create premium AI voices in any style and language with the most powerful AI speech tool ever. Clone your voice and generate voiceovers in minutes with our AI voice generator.
Mistral 7B Tutorial: Step-by-Step Guide for Using Mistral 7B
The tutorial covers accessing, quantizing, fine-tuning, merging, and saving this powerful 7.3 billion parameter open-source language model.
Bring Your Own Data to LLMs Using LangChain & LlamaIndex
Unlocking the Power of Large Language Models — GenAI, LLMs, RAG — ChatGPT
Ask Your Web Pages Using Mistral-7b & LangChain
Chat with Web Pages — Mistral-7b, Hugging Face, LangChain, ChromaDB
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Learn to Build — Towards AI Community Newsletter #2 – Towards AI
Originally published on Towards AI. What a weekend and week in AI… You missed out if you haven’t followed the OpenAI drama over the past few days. Something unbelievable...