ToolBench/ToolLLaMA-7b-v1
TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:4kPublished:Jul 28, 2023License:apache-2.0Architecture:Transformer0.0K Open Weights Cold
ToolBench/ToolLLaMA-7b-v1 is a 7 billion parameter language model, fine-tuned from LLaMA-7b, specifically designed for tool-use capabilities. Developed as part of the ToolBench project, this model excels at understanding and executing tasks that require external tools. Its primary application is in scenarios demanding complex reasoning and interaction with various APIs or functions.
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ToolLLaMA-7b-v1: A Tool-Oriented Language Model
ToolLLaMA-7b-v1 is a 7 billion parameter language model, building upon the LLaMA-7b architecture, and specifically fine-tuned for enhanced tool-use capabilities. This model is a core component introduced by the ToolBench project, which focuses on developing and evaluating large language models' ability to effectively utilize external tools.
Key Capabilities
- Tool Integration: Designed to seamlessly integrate and interact with a wide array of external tools and APIs.
- Task Execution: Proficient in understanding complex instructions and breaking them down into sub-tasks that can be solved by invoking appropriate tools.
- Fine-tuned for ToolBench: Benefits from training on a new version of data within the ToolBench framework, optimizing its performance for tool-augmented tasks.
Good For
- Automated Task Completion: Ideal for applications requiring an LLM to perform actions beyond simple text generation, such as data retrieval, calculations, or system control.
- Agentic AI Systems: A strong candidate for building AI agents that can autonomously interact with their environment through tools.
- Research in Tool-Augmented LLMs: Provides a robust base for further research and development in the field of language models capable of tool utilization.