oveja1122/toolcalling-merged-demo
The oveja1122/toolcalling-merged-demo is a 2 billion parameter Qwen3-based causal language model, fine-tuned by oveja1122. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for tool-calling applications, leveraging its efficient fine-tuning process to provide specialized functionality.
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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.