How to deply Ollama & open web-ui on your laptop

How to deploy Ollama

 Installation:

• Download Ollama: Get the Ollama package from the GitHub repository. 
• Install Dependencies: Ensure you have any required dependencies, including libraries for your specific model. 
Verify Installation: Use ollama --version to confirm Ollama is installed correctly. 

2. Model Deployment and Usage:

Pull the Model: Use the ollama pull <model_name> command to download the desired model. 
Run the Model: Use ollama run <model_name> to initiate the model's execution. 
Interacting with the Model: Ollama provides an API at http://localhost:11434/api/generate for interacting with the model. 
Optional: Web UI: Explore Open WebUI for a user-friendly interface to manage and interact with models. 
Optional: Custom Applications: Build custom applications using libraries like FastAPI and Gradio to integrate Ollama models into your workflows. 

How to deploy open-webui

Open WebUI is an extensible, feature-rich, and user-friendly self-hosted AI platform designed to operate entirely offline. It supports various LLM runners like Ollama and OpenAI-compatible APIs, with built-in inference engine for RAG, making it a powerful AI deployment solution.

How to Install 🚀

Installation via Python pip 🐍

Open WebUI can be installed using pip, the Python package installer. Before proceeding, ensure you're using Python 3.11 to avoid compatibility issues.

1. Install Open WebUI: Open your terminal and run the following command to install Open WebUI:

   pip install open-webui

2. Running Open WebUI: After installation, you can start Open WebUI by executing:

   open-webui serve

This will start the Open WebUI server, which you can access at http://localhost:8080

To upgrade the Open-webui components

pip install open-webui --upgrade

Free online courses from Nvidia

NVIDIA just released FREE online courses in AI.

Here are 5 courses you can't afford to miss:

__________

1. Generative AI Explained
What you'll learn:

• Generative AI and how it works.

• Various Generative AI applications.

• Challenges and opportunities in Generative AI
Link: https://lnkd.in/gTAJ-sKa
__________

2. Building A Brain in 10 Minutes
What you'll learn:

• Exploring how neural networks use data to learn

• Understanding the math behind a neuron

Link: https://lnkd.in/gvVrqwZF




__________




3. Augment your LLM with Retrieval Augmented Generation:




What you'll learn:




• Basics of Retrieval Augmented Generation

• RAG retrieval process

• NVIDIA AI Foundations and RAG model components

Link: https://lnkd.in/g8hYube9

__________

4. AI in the Data Center:

What you'll learn:

• AI use cases, Machine Learning, Deep Learning, and their workflows.

• GPU architecture and its impact on AI.

• Deep learning frameworks, and deployment considerations.

Link: https://lnkd.in/gvNzawxe
__________

5. Accelerate Data Science Workflows with Zero Code Changes:

What you'll learn:

• Learn benefits of unified CPU and GPU workflows

• GPU-accelerate data processing and ML without code changes

• Experience faster processing times

Link: https://lnkd.in/gRmxxVn8



𝐅𝐑𝐄𝐄 𝐨𝐧𝐥𝐢𝐧𝐞 𝐜𝐨𝐮𝐫𝐬𝐞𝐬 𝐢𝐧 𝐀𝐈 𝐲𝐨𝐮 𝐜𝐚𝐧'𝐭 𝐦𝐢𝐬𝐬 🔥

All courses can be found here: https://lnkd.in/dahEz8tx

1️⃣ Easily Develop Advanced 3D Layout Tools on NVIDIA Omniverse https://lnkd.in/dsXcjeV4


2️⃣ How to Build Custom 3D Scene Manipulator Tools on NVIDIA Omniverse https://lnkd.in/dhr6vKZY


3️⃣ AI in the Data Center

https://lnkd.in/d3DdNxq9


4️⃣ Building a Brain in 10 Minutes

https://lnkd.in/gtWMPJZK


5️⃣ Networking Introduction

https://lnkd.in/dTsJ9iDa


6️⃣ Mastering Recommender Systems https://lnkd.in/gXYVgvKg


7️⃣ Accelerate Data Science Workflows with Zero Code Changes https://lnkd.in/ghNhRjPg


8️⃣ Building RAG Agents with LLMs

https://lnkd.in/gZVuM679


9️⃣ Generative AI Explained

https://lnkd.in/gFxY6kZh


🔟 Augment your LLM Using Retrieval Augmented Generation https://lnkd.in/g87DCW_V

______

🤳 Contact us if you made a great AI tool to be featured: https://lnkd.in/d5VZ-W8H

_________




💡Share this knowledge with your network to help others.