Glaiveai

Models by this creator

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glaive-function-calling-v1

glaiveai

Total Score

64

glaive-function-calling-v1 is a 2.7B parameter AI model trained by glaiveai that has similar function calling abilities as GPT-3.5 and GPT-4. It is built on top of the replit/replit-code-v1-3b model and can have multi-turn conversations, intelligently choosing when to execute a provided function based on the conversation. Similar models include gorilla-openfunctions-v1 and gorilla-openfunctions-v2, which also provide function calling capabilities. Model inputs and outputs Inputs A provided function specification in JSON format at the start of the conversation User prompts that can reference the provided functions Outputs Function calls in the format {...} Responses that incorporate the results of the executed functions Capabilities The glaive-function-calling-v1 model can intelligently decide when to execute a provided function based on the conversation context. It supports multi-turn interactions, allowing the user to build upon previous function calls. What can I use it for? The glaive-function-calling-v1 model could be useful for building conversational applications that allow users to interact with and execute specific functions, such as planning a vacation, booking a ride, or retrieving information. Its ability to have multi-turn dialogues and choose when to execute functions makes it well-suited for interactive, task-oriented applications. Things to try One interesting thing to try with glaive-function-calling-v1 would be to provide it with a diverse set of functions and see how it handles more complex, multi-step request flows. You could also experiment with different types of functions beyond the vacation planning example, to see how the model generalizes to other domains.

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Updated 5/17/2024

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glaive-coder-7b

glaiveai

Total Score

53

The glaive-coder-7b is a 7 billion parameter code model developed by glaiveai that has been trained on a dataset of ~140k programming-related problems and solutions. This model is a fine-tuned version of the CodeLLama-7b model, giving it enhanced capabilities for code-related tasks. The glaive-coder-7b model is similar to other code-focused models like glaive-function-calling-v1 and CodeShell-7B, which also aim to provide powerful code generation and assistance capabilities. However, the glaive-coder-7b model has been specifically trained on a larger dataset of programming problems, potentially giving it an advantage for certain coding-related tasks. Model inputs and outputs Inputs Prompts**: The model accepts prompts in a specific format, where the instruction is wrapped in [INST] tags and the user message is provided afterwards. Outputs Code and text responses**: The model generates code and text responses based on the provided prompt, with the model's output wrapped in `` tags. Capabilities The glaive-coder-7b model is capable of both single-instruction following and multi-turn conversations related to coding tasks. It has been trained to serve as a code assistant, helping with a variety of programming-related activities such as code generation, debugging, and task completion. What can I use it for? The glaive-coder-7b model can be a valuable tool for developers and programmers, providing assistance with a wide range of coding-related tasks. Some potential use cases include: Generating code snippets and solutions for programming challenges Helping with code refactoring and optimization Assisting with debugging and troubleshooting Providing explanations and guidance for programming concepts The model's Code Models Arena initiative also aims to gather user feedback and preferences to help improve the performance and usefulness of code-focused AI models like the glaive-coder-7b. Things to try One interesting aspect of the glaive-coder-7b model is its ability to engage in multi-turn conversations, allowing users to iteratively refine and build upon their coding-related tasks. This could be particularly useful for complex programming problems that require a more interactive and collaborative approach. Additionally, the model's strong performance on benchmarks like HumanEval and MBPP suggests that it may be a valuable tool for tasks like algorithmic problem-solving and code generation. Developers could explore using the glaive-coder-7b model to generate initial code solutions and then refine them further. Overall, the glaive-coder-7b model appears to be a capable and versatile tool for programmers and developers, with the potential to streamline various coding-related workflows and tasks.

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Updated 5/17/2024