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Gorilla

Gorilla is a GitHub project focused on training and evaluating large language models (LLMs) for function calls, also known as tool calls. It provides a framework for developers to enhance the performance and accuracy of LLMs in executing specific functions.

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Gorilla is a GitHub repository dedicated to the training and evaluation of large language models (LLMs) specifically for function calls, which are often referred to as tool calls. This project aims to improve the ability of LLMs to perform specific functions accurately and efficiently. By focusing on function calls, Gorilla provides a framework that allows developers to enhance the performance of LLMs in executing tasks that require precise function execution.

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The repository offers a comprehensive set of tools and resources for developers interested in working with LLMs. It includes training data, evaluation metrics, and guidelines for optimizing the performance of LLMs in function call scenarios. Gorilla is particularly useful for developers who are looking to integrate LLMs into applications that require high accuracy in function execution.

Gorilla is an open-source project, making it accessible to a wide range of developers and researchers. The repository encourages collaboration and contributions from the community to further improve the capabilities of LLMs in handling function calls. With its focus on function call optimization, Gorilla serves as a valuable resource for those looking to leverage LLMs in specialized applications.

The project is maintained on GitHub, providing a platform for developers to access the code, contribute to its development, and engage with a community of like-minded individuals. Gorilla's open-source nature ensures that it remains a dynamic and evolving project, benefiting from the collective expertise of its contributors.

  • CategoryCoding & Development
  • Pricing ModelOpen source
  • DeploymentCloud
  • PlatformsWeb

  • Training LLMs for function calls

  • Evaluating LLM performance

  • Open-source framework

  • Community collaboration

  • Function call optimization

  • Comprehensive tools and resources

  • Guidelines for LLM integration

  • Accessible on GitHub

  1. Clone: Download the repository from GitHub

  2. Install dependencies: Set up necessary libraries and tools

  3. Configure: Adjust settings for specific function call scenarios

  4. Execute: Run training and evaluation scripts

  5. Optimize: Fine-tune LLM performance for function calls

  • LLM Training
  • Function Call Evaluation
  • Open-Source Collaboration
  • Application Integration
  • Community Engagement

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