Apr 21, 2024
How to Run Llama 3 Locally on Your PC
You don't necessarily need to be connected to the internet to use Llama 3. It can be run locally on your M1/M2 Mac, Windows, or Linux. Here's an example of how you can use the local version of Llama 3. This article describes three open-source platforms that will help you run Llama 3 on your personal devices.
Shortly after the release of Meta AI Llama 3, several options for local usage have become available. This article provides an overview of three open-source tools that enable you to operate Llama 3 on your personal devices operated by Mac, Windows, and Linux.
Ollama
Open WebUI
LM Studio
Ollama
Platforms: Mac, Linux, Windows (Beta)
Ollama is a complimentary open-source application that enables the operation of various large language models, including Llama 3, on your own machine, even if it's not the most powerful. Leveraging the enhancements from llama.cpp, an open-source library, Ollama allows you to run LLMs locally without demanding extensive hardware. Additionally, it features a kind of package manager, making it possible to swiftly and efficiently download and deploy LLMs with just a single command.
To get started with the Ollama CLI, download the application from ollama.ai/download. It is compatible with the three major operating systems, with the Windows version currently in "preview" (a gentler term for beta).
Once installed, simply open your terminal. The command to run Ollama is the same across all platforms.
Run this in your terminal:
# download the 7B model (3.8 GB)
ollama run llama3
# or for specific versions
Then, you can start chatting with it:
ollama run llama3
>>> hi Hello! How can I help you today
Open WebUI with Docker
Platforms: Mac, Linux, Windows
Open WebUI offers a flexible, self-hosted user interface that operates fully within Docker. It's compatible with Ollama as well as other OpenAI compatible large language models (LLMs), such as LiteLLM or customized OpenAI APIs.
Docker Desktop simplifies the process by providing a one-click-install application for Mac, Linux, or Windows systems, allowing you to build, share, and run containerized apps and microservices easily.
If you've already set up Docker and Ollama on your PC, getting started is straightforward.
docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main
Then just go to http://localhost:3000, set up an account, and begin chatting!
Note: If this is your first time using Llama 3 with Docker, you will need to download the models. To do this, simply click on the settings icon after selecting your name at the bottom left corner of the screen. Then, select "models" from the left side of the pop-up window and enter a model name from the Ollama registry to begin downloading.
You can choose between a wide range of models, including Llama 3, Lama 2, Mistral, and others.
LM Studio
Platforms: Mac, Linux (Beta), Windows
LM Studio uses the llama.cpp project and can handle different models like ggml Llama, MPT, and StarCoder from Hugging Face.
Steps:
1. Download LM Studio from its website and install.
2. Download Llama 3 8B Instruct model.
LM Studio has a chat interface built into it to help users interact better.
Each method lets you run Llama 3 on your PC or Mac in different ways, through either Meta AI, Open WebUI, or LM Studio, depending on your tech skills and needs. Just follow the steps and use the tools provided to start using Llama 3 effectively.
Related articles
– Guide to running llama 2 locally
Apr 21, 2024
How to Run Llama 3 Locally on Your PC
You don't necessarily need to be connected to the internet to use Llama 3. It can be run locally on your M1/M2 Mac, Windows, or Linux. Here's an example of how you can use the local version of Llama 3. This article describes three open-source platforms that will help you run Llama 3 on your personal devices.
Shortly after the release of Meta AI Llama 3, several options for local usage have become available. This article provides an overview of three open-source tools that enable you to operate Llama 3 on your personal devices operated by Mac, Windows, and Linux.
Ollama
Open WebUI
LM Studio
Ollama
Platforms: Mac, Linux, Windows (Beta)
Ollama is a complimentary open-source application that enables the operation of various large language models, including Llama 3, on your own machine, even if it's not the most powerful. Leveraging the enhancements from llama.cpp, an open-source library, Ollama allows you to run LLMs locally without demanding extensive hardware. Additionally, it features a kind of package manager, making it possible to swiftly and efficiently download and deploy LLMs with just a single command.
To get started with the Ollama CLI, download the application from ollama.ai/download. It is compatible with the three major operating systems, with the Windows version currently in "preview" (a gentler term for beta).
Once installed, simply open your terminal. The command to run Ollama is the same across all platforms.
Run this in your terminal:
# download the 7B model (3.8 GB)
ollama run llama3
# or for specific versions
Then, you can start chatting with it:
ollama run llama3
>>> hi Hello! How can I help you today
Open WebUI with Docker
Platforms: Mac, Linux, Windows
Open WebUI offers a flexible, self-hosted user interface that operates fully within Docker. It's compatible with Ollama as well as other OpenAI compatible large language models (LLMs), such as LiteLLM or customized OpenAI APIs.
Docker Desktop simplifies the process by providing a one-click-install application for Mac, Linux, or Windows systems, allowing you to build, share, and run containerized apps and microservices easily.
If you've already set up Docker and Ollama on your PC, getting started is straightforward.
docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main
Then just go to http://localhost:3000, set up an account, and begin chatting!
Note: If this is your first time using Llama 3 with Docker, you will need to download the models. To do this, simply click on the settings icon after selecting your name at the bottom left corner of the screen. Then, select "models" from the left side of the pop-up window and enter a model name from the Ollama registry to begin downloading.
You can choose between a wide range of models, including Llama 3, Lama 2, Mistral, and others.
LM Studio
Platforms: Mac, Linux (Beta), Windows
LM Studio uses the llama.cpp project and can handle different models like ggml Llama, MPT, and StarCoder from Hugging Face.
Steps:
1. Download LM Studio from its website and install.
2. Download Llama 3 8B Instruct model.
LM Studio has a chat interface built into it to help users interact better.
Each method lets you run Llama 3 on your PC or Mac in different ways, through either Meta AI, Open WebUI, or LM Studio, depending on your tech skills and needs. Just follow the steps and use the tools provided to start using Llama 3 effectively.
Related articles
– Guide to running llama 2 locally
Apr 21, 2024
How to Run Llama 3 Locally on Your PC
You don't necessarily need to be connected to the internet to use Llama 3. It can be run locally on your M1/M2 Mac, Windows, or Linux. Here's an example of how you can use the local version of Llama 3. This article describes three open-source platforms that will help you run Llama 3 on your personal devices.
Shortly after the release of Meta AI Llama 3, several options for local usage have become available. This article provides an overview of three open-source tools that enable you to operate Llama 3 on your personal devices operated by Mac, Windows, and Linux.
Ollama
Open WebUI
LM Studio
Ollama
Platforms: Mac, Linux, Windows (Beta)
Ollama is a complimentary open-source application that enables the operation of various large language models, including Llama 3, on your own machine, even if it's not the most powerful. Leveraging the enhancements from llama.cpp, an open-source library, Ollama allows you to run LLMs locally without demanding extensive hardware. Additionally, it features a kind of package manager, making it possible to swiftly and efficiently download and deploy LLMs with just a single command.
To get started with the Ollama CLI, download the application from ollama.ai/download. It is compatible with the three major operating systems, with the Windows version currently in "preview" (a gentler term for beta).
Once installed, simply open your terminal. The command to run Ollama is the same across all platforms.
Run this in your terminal:
# download the 7B model (3.8 GB)
ollama run llama3
# or for specific versions
Then, you can start chatting with it:
ollama run llama3
>>> hi Hello! How can I help you today
Open WebUI with Docker
Platforms: Mac, Linux, Windows
Open WebUI offers a flexible, self-hosted user interface that operates fully within Docker. It's compatible with Ollama as well as other OpenAI compatible large language models (LLMs), such as LiteLLM or customized OpenAI APIs.
Docker Desktop simplifies the process by providing a one-click-install application for Mac, Linux, or Windows systems, allowing you to build, share, and run containerized apps and microservices easily.
If you've already set up Docker and Ollama on your PC, getting started is straightforward.
docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main
Then just go to http://localhost:3000, set up an account, and begin chatting!
Note: If this is your first time using Llama 3 with Docker, you will need to download the models. To do this, simply click on the settings icon after selecting your name at the bottom left corner of the screen. Then, select "models" from the left side of the pop-up window and enter a model name from the Ollama registry to begin downloading.
You can choose between a wide range of models, including Llama 3, Lama 2, Mistral, and others.
LM Studio
Platforms: Mac, Linux (Beta), Windows
LM Studio uses the llama.cpp project and can handle different models like ggml Llama, MPT, and StarCoder from Hugging Face.
Steps:
1. Download LM Studio from its website and install.
2. Download Llama 3 8B Instruct model.
LM Studio has a chat interface built into it to help users interact better.
Each method lets you run Llama 3 on your PC or Mac in different ways, through either Meta AI, Open WebUI, or LM Studio, depending on your tech skills and needs. Just follow the steps and use the tools provided to start using Llama 3 effectively.
Related articles
– Guide to running llama 2 locally
Apr 21, 2024
How to Run Llama 3 Locally on Your PC
You don't necessarily need to be connected to the internet to use Llama 3. It can be run locally on your M1/M2 Mac, Windows, or Linux. Here's an example of how you can use the local version of Llama 3. This article describes three open-source platforms that will help you run Llama 3 on your personal devices.
Shortly after the release of Meta AI Llama 3, several options for local usage have become available. This article provides an overview of three open-source tools that enable you to operate Llama 3 on your personal devices operated by Mac, Windows, and Linux.
Ollama
Open WebUI
LM Studio
Ollama
Platforms: Mac, Linux, Windows (Beta)
Ollama is a complimentary open-source application that enables the operation of various large language models, including Llama 3, on your own machine, even if it's not the most powerful. Leveraging the enhancements from llama.cpp, an open-source library, Ollama allows you to run LLMs locally without demanding extensive hardware. Additionally, it features a kind of package manager, making it possible to swiftly and efficiently download and deploy LLMs with just a single command.
To get started with the Ollama CLI, download the application from ollama.ai/download. It is compatible with the three major operating systems, with the Windows version currently in "preview" (a gentler term for beta).
Once installed, simply open your terminal. The command to run Ollama is the same across all platforms.
Run this in your terminal:
# download the 7B model (3.8 GB)
ollama run llama3
# or for specific versions
Then, you can start chatting with it:
ollama run llama3
>>> hi Hello! How can I help you today
Open WebUI with Docker
Platforms: Mac, Linux, Windows
Open WebUI offers a flexible, self-hosted user interface that operates fully within Docker. It's compatible with Ollama as well as other OpenAI compatible large language models (LLMs), such as LiteLLM or customized OpenAI APIs.
Docker Desktop simplifies the process by providing a one-click-install application for Mac, Linux, or Windows systems, allowing you to build, share, and run containerized apps and microservices easily.
If you've already set up Docker and Ollama on your PC, getting started is straightforward.
docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main
Then just go to http://localhost:3000, set up an account, and begin chatting!
Note: If this is your first time using Llama 3 with Docker, you will need to download the models. To do this, simply click on the settings icon after selecting your name at the bottom left corner of the screen. Then, select "models" from the left side of the pop-up window and enter a model name from the Ollama registry to begin downloading.
You can choose between a wide range of models, including Llama 3, Lama 2, Mistral, and others.
LM Studio
Platforms: Mac, Linux (Beta), Windows
LM Studio uses the llama.cpp project and can handle different models like ggml Llama, MPT, and StarCoder from Hugging Face.
Steps:
1. Download LM Studio from its website and install.
2. Download Llama 3 8B Instruct model.
LM Studio has a chat interface built into it to help users interact better.
Each method lets you run Llama 3 on your PC or Mac in different ways, through either Meta AI, Open WebUI, or LM Studio, depending on your tech skills and needs. Just follow the steps and use the tools provided to start using Llama 3 effectively.
Related articles
– Guide to running llama 2 locally
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© 2023 Writingmate.ai
© 2023 Writingmate.ai
© 2023 Writingmate.ai