Check out the cool LLM Apps with RAG and AI agents in this GitHub Repo. P.S: Don't forget to star the repo to show your support and get future updates
OPEN SOURCE
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Ollama and Open WebUI: Offline LLM Chat Interface
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3. Ollama + Open WebUI
— Shubham Saboo (@Saboo_Shubham_) 13 mai 2024
Combine Ollama with Open WebUI for a smooth, offline experience with a ChatGPT-like interface.
It works with various LLM runners and OpenAI-compatible APIs, all without needing the internet. pic.twitter.com/F7g1lNp1Xw3. Ollama + Open WebUI Combine Ollama with Open WebUI for a smooth, offline experience with a ChatGPT-like interface. It works with various LLM runners and OpenAI-compatible APIs, all without needing the internet.
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Ollama: Run Multimodal AI Models Locally on Your Computer
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2. Ollama
— Shubham Saboo (@Saboo_Shubham_) 13 mai 2024
Ollama is an open-source project that offers an easy way to download and run multimodal AI models such as llava and bakllava on your computer.
To get started, install Ollama and run this command in your terminal: 'ollama run llava' pic.twitter.com/wiRoxwgnbD2. Ollama Ollama is an open-source project that offers an easy way to download and run multimodal AI models such as llava and bakllava on your computer. To get started, install Ollama and run this command in your terminal: 'ollama run llava'
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LM Studio: Run Multimodal AI Models Offline Locally
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1. LM Studio
— Shubham Saboo (@Saboo_Shubham_) 13 mai 2024
LM Studio lets you operate multimodal AI models offline right on your desktop. It has a chat interface too.
Just download LM Studio, install it, and you're set to run any open-source multimodal model without an internet connection. pic.twitter.com/UozjDIDSqK1. LM Studio LM Studio lets you operate multimodal AI models offline right on your desktop. It has a chat interface too. Just download LM Studio, install it, and you're set to run any open-source multimodal model without an internet connection.
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Run Multimodal AI Models Locally Free Without Internet
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3 ways to run Multimodal AI models like GPT-4 Vision locally on your computer (100% free and without internet):
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Groq Supports Llama 3 Hackathon with Judge Jonathan Ross
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Our workshop is over, coding is in full swing, and soon our very own @JonathanRoss321 will help judge the final round in the @AIatMeta and @cerebral_valley Llama 3 hackathon. Can't wait to see what everyone built on Groq!
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Essential Machine Learning Tools and Libraries Guide
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Practical Machine Learning Tools and Libraries. #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode https://
geni.us/Practical-ML-T
ools
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IBM Releases Granite Code Models Across 116 Programming Languages
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10). Granite Code Models – introduce Granite, a series of code models trained with code written in 116 programming languages; it consists of models ranging in size from 3 to 34 billion parameters, suitable for applications ranging from application modernization tasks to on-device
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MAmmoTH2: Harvesting Web Data to Enhance LLM Reasoning
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9). MAmmoTH2 – harvest 10 million naturally existing instruction data from the pre-training web corpus to enhance LLM reasoning; the approach first recalls relevant documents, extracts instruction-response pairs, and then refines the extracted pairs using open-source LLMs;
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Building vs Reusing: Learning and Optimization for Your Tech Stack
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Totally agree Sometimes it’s better to reuse existing stuff, but sometimes it’s better to build your own thing for first principles. You will learn a lot, you get more free in what you can do with it, you can optimize it for your use cases, and you build your own niche. Been