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Well known llms run locally

You are looking for some well-known large language models (LLMs) that you can run locally on your workstation. Based on the hardware specifications of your system, which includes a powerful Intel Core i7-12700F CPU, 64GB of RAM, and a capable AMD Radeon RX 7700 XT GPU, you have a strong setup for running local LLMs.

Here are several well-known LLMs that should work well locally on your system:

1. LLaMA (LLaMA 2 and LLaMA 3)

LLaMA models are highly popular and efficient, especially for local deployment. The LLaMA family includes various versions, such as LLaMA 2 and the newer LLaMA 3. These models are available in different sizes (e.g., 7B, 13B, 30B, and 70B parameters), with smaller models like 7B being more suitable for local use without requiring excessive resources.

  • Best for: General-purpose tasks like text generation and conversation.
  • Tools: You can use llama.cpp to run these models efficiently on your hardware[5][6].

2. GPT4All

GPT4All is another excellent option for running LLMs locally. It is designed to be lightweight and privacy-focused, making it ideal for personal use without requiring an internet connection. GPT4All supports multiple models and can be easily installed on Linux-based systems like yours.

  • Best for: Privacy-focused applications and general conversational tasks.
  • Tools: Comes with a user-friendly GUI and supports various models[2][5].

3. Mistral

Mistral is a newer model that has gained popularity due to its efficiency and performance. It is available in smaller sizes like 7B or combined mixtures of experts (MoE) models, which can run well on systems with decent hardware like yours.

  • Best for: High-performance tasks with lower resource consumption.
  • Tools: Can be run using llama.cpp or integrated with other tools like Ollama[2][6].

4. Vicuna

Vicuna is a fine-tuned version of LLaMA that has been optimized for conversational tasks. It performs very well in chatbot scenarios and is considered one of the best open-source alternatives to proprietary models like ChatGPT.

  • Best for: Conversational AI and chatbots.
  • Tools: Can be run using llama.cpp or other local frameworks[6].

5. Ollama

Ollama is a tool specifically designed to run local LLMs easily through the terminal or with Python integration. It supports various models like LLaMA, Mistral, Falcon, and others. This tool simplifies the process of running these models locally without needing extensive setup.

  • Best for: Easy access to multiple open-source models with minimal setup.
  • Tools: Ollama provides an intuitive interface for running different models[5][6].

Conclusion:

Given your hardware setup, you could comfortably run a variety of LLMs locally. Start by experimenting with smaller models like LLaMA 7B or Mistral 7B to ensure smooth performance before moving to larger ones if needed.

For installation:

  • Use llama.cpp or Ollama for easy setup.
  • Consider GPT4All if you prioritize privacy.

These tools should work efficiently on your system while giving you flexibility in choosing the right model for your needs!

The above text was generated by a large language model (LLM) and its accuracy has not been validated. This page is part of 'LLMs-on-LLMs,' a Github repository by Daniel Rosehill which explores how curious humans can use LLMs to better their understanding of LLMs and AI. However, the information should not be regarded as authoritative and given the fast pace of evolution in LLM technology will eventually become deprecated. This footer was added at 16-Nov-2024.