Model Overview

The young924/toolcalling-merged-demo is a 2 billion parameter Qwen3-based language model, developed by young924. It is fine-tuned from the unsloth/Qwen3-1.7B-unsloth-bnb-4bit base model, indicating an optimization for efficiency and performance within its parameter class. The model was trained using Unsloth and Huggingface's TRL library, which facilitated a 2x faster fine-tuning process.

Key Characteristics

• Architecture: Qwen3-based causal language model.
• Parameter Count: 2 billion parameters.
• Context Length: Supports a context length of 32768 tokens.
• Training Efficiency: Fine-tuned with Unsloth and Huggingface's TRL library for accelerated training.

Primary Use Case

This model is specifically designed and fine-tuned for tool-calling applications. Its architecture and training methodology suggest a focus on accurately interpreting user requests and generating appropriate tool calls, making it suitable for integration into systems requiring automated function execution or API interaction.