diwkdiwk/toolcalling-merged-demo

TEXT GENERATIONConcurrency Cost:1Model Size:2BQuant:BF16Ctx Length:32kPublished:Apr 9, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

The diwkdiwk/toolcalling-merged-demo is a 2 billion parameter Qwen3-based causal language model developed by diwkdiwk, fine-tuned for tool-calling capabilities. This model was trained using Unsloth and Huggingface's TRL library, enabling faster training. With a 32768 token context length, it is optimized for applications requiring efficient function calling and integration with external tools.

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Model Overview

The diwkdiwk/toolcalling-merged-demo is a 2 billion parameter Qwen3-based language model developed by diwkdiwk. It has been specifically fine-tuned for tool-calling functionalities, making it suitable for applications that require the model to interact with external tools or APIs.

Key Capabilities

  • Tool Calling: Designed to understand and generate calls to external functions or tools.
  • Efficient Training: Leverages Unsloth and Huggingface's TRL library for accelerated training, building upon the unsloth/Qwen3-1.7B-unsloth-bnb-4bit base model.
  • Qwen3 Architecture: Benefits from the underlying Qwen3 architecture, providing a robust foundation for language understanding and generation.

Good For

  • Developing agents that can interact with external systems.
  • Applications requiring structured output for function invocation.
  • Experimenting with efficient fine-tuning techniques for Qwen3 models.