OLLAMA | How To Run UNCENSORED AI Models on Windows
TLDRIn this informative video, the viewer is guided through the process of installing and running OLLAMA, an open-source AI model, on a Windows desktop. The host demonstrates how to download OLLAMA from ama.com, install it, and use the 'AMA help' command in Powershell to explore available commands. The video focuses on the 'run', 'pull', and 'remove' commands, showing how to download and run the uncensored Llama 2 model, as well as other models like Code Llama and Lava for coding assistance and multimodal tasks respectively. The host also explains how to list installed models, remove them, and test the functionality of the models locally without relying on third-party providers. The video concludes with an invitation to learn more about building a chatbot using OLLAMA.
Takeaways
- 💻 To run OLLAMA on Windows, first visit ama.com, download the Windows version, and install it on your PC.
- 🔍 After installation, you can find the OLLAMA icon in the bottom toolbar, indicating successful setup.
- 📝 Open Powershell to run different OLLAMA commands, starting with `AMA help` to view available commands.
- 🌐 Browse the AMA website to find and select models you want to use, like Llama 2 uncensored.
- 📥 Use the `AMA run
` command in Powershell to download and run a model locally, which also pulls the model if it's not already on your PC. - ⏳ Download times for models depend on your internet speed, and running the model for the first time may take longer due to loading into memory.
- 📋 The `AMA list` command shows all the models currently installed on your laptop.
- 🔄 The `AMA pull
` command allows you to download a model without running it. - 🗑️ To remove a model from your system, use the `AMA RM
` command. - 📈 Models like Code LLama are specialized for tasks such as coding and debugging, while others like Lava are multimodal, capable of analyzing images and generating text.
- 🚀 OLLAMA enables you to run open-source models locally, providing functionality without relying on third-party providers, given you have sufficient GPU power.
Q & A
What is the first step to set up OLLAMA on a Windows desktop?
-The first step is to open your web browser, navigate to ama.com, and download the OLLAMA setup for Windows from the website.
What happens after downloading the OLLAMA setup for Windows?
-After downloading, you should find 'ama setup' in your downloads folder, double-click on it to start the installation process.
How can you check if OLLAMA has been successfully installed on your Windows PC?
-You can check by going to the bottom taskbar, clicking on 'show hidden items', and looking for the OLLAMA icon (a little llama head).
What is the first command to run in Powershell to get a list of available OLLAMA commands?
-The first command to run in Powershell is 'AMA help', which will show all the available commands.
How do you find and download different models to run locally on your PC using OLLAMA?
-You can find and download models by going to the OLLAMA website, clicking on 'models', selecting the desired model, and using the provided command to download and run it locally.
What command is used to run a specific model like Llama 2 uncensored on your local PC?
-The command to run a specific model is 'AMA run' followed by the model name, for example, 'AMA run llama 2-uncensor'.
How can you list all the models that you have on your laptop?
-You can list all the models by running the 'AMA list' command in Powershell or the command line.
What is the 'pull' command in OLLAMA used for?
-The 'pull' command is used to download a specific model without running it. It's useful when you want to download a model for later use.
How do you remove a model from your laptop using OLLAMA?
-To remove a model, you use the 'AMA RM' command followed by the model name, for example, 'AMA RM llama 2-latest'.
What is the 'lava' model capable of doing?
-The 'lava' model is a multimodal model that can analyze images, describe what's in them, and also function as a normal text-generating model.
How can you run the 'code llama' model to get sample code?
-You can run the 'code llama' model by typing 'AMA run code llama' in Powershell or the command line and then asking for sample code or providing a coding-related query.
What is the benefit of using OLLAMA for running AI models locally?
-OLLAMA allows you to download and run open-source models locally on your laptop without needing to rely on third-party providers, as long as you have sufficient GPU power.
Outlines
🚀 Installing Olama on Windows
The video begins with instructions on how to install Olama on a Windows desktop. It guides viewers to download the software from ama.com, navigate to the downloads folder, and initiate the installation process. After successful installation, the Olama icon appears in the taskbar, allowing access to features like viewing locks and quitting the application. The presenter then demonstrates how to use Powershell to run various Olama commands, starting with 'AMA help' to list available commands, focusing on 'run', 'pull', and 'remove'.
📚 Exploring and Running Olama Models
The video continues with a demonstration of how to find and run different models using the Olama platform. It shows how to access the AMA website to browse available models, such as Llama 2 and Lava, and provides information on model parameters, updates, and sizes. The presenter then illustrates the process of pulling down a model (Llama 2 uncensored) to the local PC, which also involves downloading it if it's not already present. After the model is downloaded, the video shows how to interact with the model by asking it a question and receiving a response.
🗄️ Managing Olama Models and Commands
The presenter proceeds to explain additional Olama commands that allow users to manage the models on their system. It covers how to list all downloaded models with 'olama list', how to pull a model without running it using 'olama pull', and how to remove a model with 'olama RM'. The video also touches on the capabilities of different models, such as Code Llama for coding assistance and Lava for multimodal inputs including image analysis. The presenter demonstrates the image analysis feature of the Lava model by asking it to describe a picture of a puppy, which it does accurately. Finally, the video concludes with a sample code generation using Code Llama, showcasing its ability to write and explain simple Python code with classes and functions.
Mindmap
Keywords
💡OLLAMA
💡Windows
💡Open Source Models
💡Installation
💡Powershell
💡Models
💡Pull Command
💡Remove Command
💡Multimodal Model
💡Code Llama
Highlights
OLLAMA is a tool for running uncensored AI models on Windows desktop.
OLLAMA website is accessible at ama.com for downloading the software.
OLLAMA for Windows is in preview but available for download.
Installation of OLLAMA is straightforward with a setup file found in the Downloads folder.
Post-installation, a llama head icon in the taskbar indicates successful setup.
Powershell or command line can be used to run different OLLAMA commands.
The 'AMA help' command lists all available OLLAMA commands.
Models can be downloaded from the AMA website and run locally on a PC.
The 'AMA run' command is used to execute models, such as the uncensored Llama 2 model.
Downloading models depends on internet speed and can be done even if the model is not already on the PC.
Once downloaded, models run locally and can perform tasks like answering questions and booking appointments.
The 'AMA list' command shows all downloaded models on the laptop.
The 'AMA pull' command allows users to download models without running them.
Models like Code Llama are designed for coding assistance, while Llava is a multimodal model that can analyze images.
The 'AMA remove' command is used to delete models from the laptop.
Llava can analyze and describe images, showcasing its multimodal capabilities.
Code Llama can generate and explain sample Python code with classes and functions.
OLLAMA enables users to run open-source models locally, providing functionality without relying on third-party providers.
Users interested in building chatbots can find tutorials on how to use OLLAMA for this purpose.