Dria-Agent-a-3B
D
Dria Agent A 3B
Overview :
Dria-Agent-a-3B is a large language model based on the Qwen2.5-Coder series, specifically tailored for agent applications. It employs a Pythonic approach to function calling, featuring advantages such as concurrent multi-function calls, free-form reasoning and actions, and instant complex solution generation. The model has excelled in various benchmarks, including the Berkeley Function Calling Leaderboard (BFCL), MMLU-Pro, and the Dria-Pythonic-Agent-Benchmark (DPAB). It has 3.09 billion parameters and supports the BF16 tensor type.
Target Users :
Designed for developers and researchers looking to utilize large language models in agent applications, it offers efficient function calling and advanced logic processing capabilities, making it ideal for scenarios that require quick development and deployment of intelligent agent systems.
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Use Cases
In intelligent customer service systems, quickly respond to user requests and execute multiple operations.
Generate complex Python scripts for automating office processes, increasing work efficiency.
In education, provide students with personalized learning plans and real-time feedback.
Features
Supports concurrent multi-function calls, enhancing interaction efficiency.
Enables free-form reasoning and actions, reducing output constraints tied to specific formats.
Can generate complex solutions instantly, implementing conditions and synchronized pipelines.
Achieved excellent results on multiple benchmarks, including BFCL, MMLU-Pro, and DPAB.
Adopts a Pythonic function calling style, enhancing the model's flexibility and scalability.
How to Use
1. Import necessary libraries, such as transformers.
2. Initialize the model using the pre-trained model and tokenizer.
3. Prepare system prompts and user queries, formatting the input as specified.
4. Generate function calling code using the model.
5. Decode and execute the generated code to obtain results.
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