9 Open Source LLMs and Agents to Watch

ODSC - Open Data Science
5 min readOct 2, 2023

In the past year, there has been a surge of interest in large language models and LLM agents. As large language models continue their assent into multiple fields, they will begin to branch off and become more domain-specific to tackle complex problems that general LLMs aren’t well suited for.

So let’s take a look at some interesting and new open-source LLMs and LLM agents that we are following:

Open Interpreter:

Open Interpreter is a project that aims to create a universal interpreter for large language models. This would allow LLMs to communicate with each other and access information from a variety of sources, allowing them to share information and collaborate on tasks with greater efficiency.

The project is still in its early stages, but it has the potential to revolutionize the way that open source LLMs are used. If successful, it could lead to LLMs being used in a wide range of new applications, from customer service to medical diagnosis.

LLama2.c:

LLama2.c is a fork of the LLM project by Andrej Karpathy. It is designed to be more efficient and easier to use than the original LLM. LLama2.c is written in C, while the original LLM is written in Python. This makes LLama2.c faster and more memory-efficient than the original LLM. LLama2.c also includes several features that make it easier to use, such as a command-line interface and a graphical user interface.

Fooocus:

Fooocus is a project that aims to create a large language model (LLM) that can focus on specific tasks. This would make it possible to use LLMs to solve problems that are too complex for other methods. For example, an LLM that is focused on the task of writing code could be used to generate code for complex software applications. Or, an LLM that is focused on the task of translating languages could be used to translate documents from one language to another.

The Fooocus project is still in its early stages, but it has the potential to revolutionize the way we use LLMs. By focusing LLMs on specific tasks, we can make them much more powerful and useful tools.

CodeLllama:

CodeLllama is an LLM agent that has been trained to write code and generate code in a variety of programming languages. Some of the languages include Python, Java, and C++. Of course it’s not a replacement for coders, what CodeLlama can do is be used to generate code for a variety of tasks, such as creating web applications, developing mobile apps, and writing scripts. Freeing up valuable time for developers to focus on more complex projects and planning.

It can also be used to generate code for specific purposes, such as generating code to implement a specific algorithm or to generate code to solve a specific problem. CodeLlama is a powerful tool that can be used by both experienced and novice programmers.

Llama-gpt:

Llama-gpt is a large language model agent that has been trained to generate text in the style of GPT-3. It can be used to create a variety of different types of content, such as blog posts, articles, and stories. This could be helpful to people such as writers, bloggers, and marketers looking to supercharge their productivity. Llama-gpt is still under development, but it has already been used to create a variety of different types of content, including blog posts, articles, and stories. It is a promising tool that has the potential to revolutionize the way content is created.

OpenTF:

OpenTF is a project that aims to create an open-source implementation of TensorFlow. This would make it possible to use TensorFlow on a wider range of platforms and would also allow for greater customization and flexibility in how TensorFlow is used.

For example, developers could use OpenTF to create their versions of TensorFlow that are optimized for specific tasks or platforms. Additionally, OpenTF could be used to create new features and functionality that are not currently available in the proprietary implementation of TensorFlow. The project aims to create an open-source implementation and would make it possible to use TensorFlow on a wider range of platforms, including those that are not supported by the current iteration

Vall-E-X:

Vall-E-X is a project that aims to create an LLM that can mimic human speech. It is still under development, but it has the potential to revolutionize the way we interact with computers. Currently, we interact with computers through a variety of interfaces, including keyboards, mice, and touchscreens. However, these interfaces are limited in their ability to convey natural human language.

The project hopes to overcome these limitations by allowing humans to interact with computers using natural language. This would make it much easier for us to give computers instructions and ask them questions. It would also make it possible for us to have more natural conversations with computers. Vall-E-X is still in its early stages of development, but it has the potential to change the way we interact with computers in the future.

AI Town:

AI Town is a project that aims to create a virtual world where LLMs can interact with each other and with humans. For example, we could see how LLMs interact with each other in a social setting, and how they respond to different prompts and questions from humans. This information could help us to better understand how LLMs learn and think, and how they can be used in a variety of applications.

Additionally, AI Town could be used to create new forms of entertainment and education. For example, we could create virtual worlds where LLMs act as tour guides, or where they provide educational content.

Seamless Communication:

Seamless Communication is a project that aims to create a system that can automatically translate between different languages. This would allow people from all over the world to communicate with each other more easily and potentially in real-time.

These are just a few of the many new LLMs and LLM agents that are being developed. LLMs have the potential to revolutionize many different industries, and we are excited to see what the future holds for this technology.

Conclusion

It’s becoming important to keep up with any and all changes associated with open source LLMs. The best place to do this is at ODSC West 2023 this October 30th to November 2nd. With a full track devoted to NLP and LLMs, you’ll enjoy talks, sessions, events, and more that squarely focus on this fast-paced field.

Confirmed sessions include:

  • Personalizing LLMs with a Feature Store
  • Understanding the Landscape of Large Models
  • Building LLM-powered Knowledge Workers over Your Data with LlamaIndex
  • General and Efficient Self-supervised Learning with data2vec
  • Towards Explainable and Language-Agnostic LLMs
  • Fine-tuning LLMs on Slack Messages
  • Beyond Demos and Prototypes: How to Build Production-Ready Applications Using Open-Source LLMs
  • Automating Business Processes Using LangChain
  • Connecting Large Language Models — Common pitfalls & challenges

What are you waiting for? Get your pass today!

Originally posted on OpenDataScience.com

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