Model Overview

The oveja1122/toolcalling-merged-demo is a specialized 2 billion parameter language model, fine-tuned by oveja1122. It is based on the Qwen3 architecture and was developed using an efficient training methodology.

Key Characteristics

• Base Model: Fine-tuned from unsloth/Qwen3-1.7B-unsloth-bnb-4bit.
• Efficient Training: Achieved 2x faster training speeds by utilizing Unsloth and Huggingface's TRL library.
• Parameter Count: Features 2 billion parameters, offering a balance between performance and computational efficiency.
• Context Length: Supports a substantial context length of 32768 tokens.

Primary Use Case

This model is specifically designed and optimized for tool-calling applications. Its fine-tuning process and underlying architecture make it suitable for scenarios where a language model needs to interact with external tools or APIs to perform tasks, providing a robust foundation for integrating AI with other systems.