hsmehta012/functiongemma-270m-it-smart-cockpit
The hsmehta012/functiongemma-270m-it-smart-cockpit model is a fine-tuned version of Google's FunctionGemma-270M-IT, a 0.3 billion parameter instruction-tuned model. It specializes in function calling and tool use, leveraging its base architecture for efficient and accurate interaction with external APIs and services. This model is optimized for integration into smart cockpit systems or similar applications requiring precise function execution based on natural language prompts. Its small size and specialized fine-tuning make it suitable for resource-constrained environments where function calling capabilities are paramount.
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Model Overview
The hsmehta012/functiongemma-270m-it-smart-cockpit model is a specialized language model, fine-tuned from google/functiongemma-270m-it. This 0.3 billion parameter model is designed for efficient function calling and interaction with external tools, making it particularly suitable for applications requiring structured outputs and API integration.
Key Capabilities
- Function Calling: Excels at interpreting natural language requests and translating them into executable function calls.
- Tool Use: Optimized for scenarios where the model needs to interact with external systems or APIs.
- Instruction Following: Inherits strong instruction-following capabilities from its base model,
functiongemma-270m-it. - Compact Size: With 0.3 billion parameters, it offers a balance of performance and efficiency, suitable for deployment in environments with limited computational resources.
Training Details
The model was fine-tuned using the TRL library with a Supervised Fine-Tuning (SFT) approach. This training methodology helps in aligning the model's responses with specific function calling formats and behaviors. The training utilized TRL: 1.9.2, Transformers: 5.13.1, Pytorch: 2.11.0+cu128, Datasets: 5.0.1, and Tokenizers: 0.22.2.