Ollama - Local Models on your machine

Sam Witteveen
8 Oct 202309:33

TLDRThe video introduces Ollama, a user-friendly tool that allows users to run large language models locally on their computers. Currently supporting Mac OS and Linux, with Windows support on the way, Ollama simplifies the process of downloading and using various language models like LLaMA-2, uncensored LLaMA, CodeLLaMA, Falcon, and Mistral. The tool is command-line based, making it accessible for technical users, and it offers features like custom prompts and model management. The host demonstrates how to install, download models, and use Ollama to generate text, including creating a custom 'Hogwarts' prompt. The video concludes with a teaser for future content on using Ollama with LangChain and loading custom models.

Takeaways

  • 🦙 Discovered: Ollama is a user-friendly tool for running large language models locally on your computer.
  • 🌐 Supported Systems: Ollama currently supports Mac OS and Linux, with Windows support on the way.
  • 📚 Variety of Models: Ollama offers support for multiple models including LLaMA-2, uncensored LLaMA, CodeLLaMA, Falcon, and Mistral.
  • 🚀 Easy Installation: Ollama allows for easy installation and setup, making it accessible to non-technical users.
  • 📈 Command Line Interface: The tool operates through a command line interface, utilizing Terminal on Mac or a similar application on Linux.
  • 🔍 Model Listing: Users can list, download, and run different models directly from the command line.
  • 📉 Memory Requirements: Ollama provides information on the memory (RAM) needed to run the selected models.
  • 🚀 Downloading Models: If a model is not installed, Ollama will download it, which may take time depending on the model size.
  • 🛠️ Custom Prompts: Users can create custom prompts for models, tailoring the model's responses to specific scenarios.
  • 🧙‍♂️ Example Usage: The script demonstrates creating a 'Hogwarts' prompt for a model to respond in character as Dumbledore.
  • 🗑️ Model Management: Ollama allows users to add, remove, and manage installed models with ease.

Q & A

  • What is the name of the tool that the speaker discovered at the LangChain offices?

    -The tool the speaker discovered is called Ollama.

  • Why did the speaker decide to make a video about Ollama?

    -The speaker decided to make a video about Ollama because it is a user-friendly way to run large language models locally, which can be a huge win for non-technical people.

  • Which operating systems does Ollama currently support?

    -Ollama currently supports Mac OS and Linux, with Windows support coming soon.

  • What is one of the key features of Ollama that the speaker found fascinating?

    -One of the key features that the speaker found fascinating is the ability to easily install a local model.

  • What is the process of using Ollama for running a model?

    -To use Ollama, you download it from the website, install it on your machine, and then use the command line to run the model. It creates an API to serve the model, which you can then interact with.

  • How does one download and install a model using Ollama?

    -To download and install a model, you run the Ollama command in the terminal, and if the model is not installed, it will pull down a manifest file and start downloading the model.

  • What is the file size of the LLaMA-2 model that the speaker downloaded?

    -The file size of the LLaMA-2 model that the speaker downloaded is 3.8 gigabytes.

  • How can you check the speed of tokens processed by the model in Ollama?

    -You can check the speed of tokens processed by setting the verbose mode in the Ollama command line interface.

  • What is a custom prompt in the context of Ollama?

    -A custom prompt in Ollama is a user-defined input that sets the context or persona for the language model to respond in, allowing for more tailored and specific interactions.

  • How can one remove a model from Ollama?

    -To remove a model from Ollama, you use the command to remove the specific model, and if it's the last model referencing certain weights, those will also be deleted.

  • What is the advantage of running models locally using Ollama?

    -The advantage of running models locally using Ollama is that it allows for faster access and interaction with the models without relying on cloud services, and it can be particularly useful for those who are not comfortable with cloud-based solutions.

  • What are some of the other models supported by Ollama apart from LLaMA-2?

    -Apart from LLaMA-2, Ollama supports models like uncensored LLaMA, CodeLLaMA, Falcon, Mistral, Vicuna, WizardCoder, and Wizard uncensored.

Outlines

00:00

🤖 Introduction to Ollama: A Local Language Model Interface

The speaker begins by recounting their experience at LangChain offices where they encountered a sticker for 'Ollama', a user-friendly tool for running large language models locally. Despite their preference for cloud-based models, they were intrigued by Ollama's simplicity in installing and running models like LLaMA-2, Mistral, and others. The speaker emphasizes the benefits for non-technical users and discusses the tool's current support for Mac OS and Linux, with Windows support on the way. The video demonstrates how to download and install Ollama, use the command line to run models, and customize prompts for a more interactive experience.

05:04

📚 Exploring Ollama's Features and Customization

The speaker continues by showcasing how to use Ollama to run different language models, including censored and uncensored versions. They demonstrate downloading a model, running it, and checking its performance in terms of tokens per second. The video also covers creating a custom prompt, using the 'Hogwarts' example to illustrate how to set up a model with specific hyperparameters and a system prompt. The speaker further explains how to list, run, and remove models within Ollama, providing a comprehensive guide on utilizing the tool for local language model experimentation.

Mindmap

Keywords

💡Ollama

Ollama is a user-friendly tool designed to run large language models locally on a computer. It is particularly beneficial for individuals who are not technically proficient, as it simplifies the process of installing and using language models without the need for cloud-based services. In the video, the speaker discusses the ease of using Ollama to install and run various models, emphasizing its utility for non-technical users.

💡Local Models

Local models refer to language models that are run directly on a user's computer rather than through a cloud service. This approach can offer privacy, reduced latency, and independence from internet connectivity. The video highlights the advantages of running models locally using Ollama, showcasing how it facilitates the use of different models without relying on cloud computing.

💡LLaMA-2

LLaMA-2 is an open-source language model mentioned in the video. It is one of the models supported by Ollama, which the speaker discusses installing and using. The LLaMA-2 model is noted for its ability to generate coherent text and is used as an example to demonstrate the functionality of Ollama in running local models.

💡Fine-tuning

Fine-tuning is a process in machine learning where a pre-trained model is further trained on a specific task or dataset to improve its performance. In the context of the video, the speaker mentions fine-tuning open-source models like LLaMA-2 and Mistral, which can be done locally using Ollama to tailor the models to specific use cases.

💡Command Line

The command line is a text-based interface used to interact with a computer's operating system. In the video, the speaker explains that Ollama operates through the command line, which is a common way to execute commands and manage tasks on MacOS and Linux systems. The command line is essential for installing, managing, and running models using Ollama.

💡API

An API, or Application Programming Interface, is a set of protocols and tools that allow different software applications to communicate with each other. The video mentions that Ollama creates an API to serve the language model once installed, enabling users to interact with the model and perform tasks such as generating text or processing data.

💡Model Manifest

A model manifest is a file that contains information about a specific model, including its version, dependencies, and other metadata. In the context of the video, the speaker describes how Ollama uses a manifest file when downloading a model, which outlines the components needed for the model to function correctly.

💡Quantized Models

Quantized models are machine learning models that have been optimized by reducing the precision of their numerical values, often to save space and improve efficiency. The video references GGML format, which is a four-bit quantized way of running models, allowing for smaller model sizes and faster processing on local machines.

💡Custom Prompt

A custom prompt is a user-defined input that guides the language model to generate specific types of responses. In the video, the speaker demonstrates creating a custom prompt named 'Hogwarts', which sets the system prompt to respond as Professor Dumbledore, providing information about Hogwarts and wizardry. This showcases the flexibility of Ollama in allowing users to tailor the model's behavior.

💡Model Removal

Model removal refers to the process of deleting a language model from the system. The video explains how to remove a model using Ollama, which is useful for managing storage space and decluttering the list of available models. The speaker demonstrates removing the 'Mario' model and notes the importance of checking for dependencies before deletion.

💡LangChain

LangChain is mentioned in the video as a tool that can be run locally against various models, including those installed via Ollama. It suggests that LangChain can be used in conjunction with Ollama to test out ideas and work with language models in a local environment, enhancing the utility of both tools for users.

Highlights

Ollama is a user-friendly tool that allows users to run large language models locally on their computers.

Currently supports Mac OS and Linux, with Windows support coming soon.

Ollama enables easy installation of local models, which is beneficial for non-technical users.

The tool supports a variety of models including LLaMA-2, uncensored LLaMA, CodeLLaMA, Falcon, and Mistral.

Users can run LangChain locally against all supported models to test out ideas.

The process of getting started with Ollama is straightforward, involving a simple download and installation.

Ollama creates an API to serve the model after installation.

The tool operates through the command line, utilizing Terminal on Mac or a similar application on Linux.

Downloading a model, such as LLaMA-2, requires downloading a manifest file followed by the model itself, which can be sizeable.

Ollama provides commands to list, download, and run models, as well as to get help and model information.

The run command in Ollama allows users to execute models with prompts or flags.

Custom prompts can be created for models, allowing for tailored interactions.

An example of a custom prompt is demonstrated with a 'Hogwarts' theme, showing the model's ability to answer in character.

Models can be added, listed, and removed through Ollama's command-line interface.

The tool provides information on the memory requirements for running different models.

Ollama supports open source, fine-tuned models and allows users to experiment with various configurations.

The video concludes with a teaser for future content on using Ollama with LangChain and loading custom models.

Create Stunning AI Art Instantly

No login. No cost. Just incredible AI images !

Create Stunning AI Art InstantlyGenerate Now