Baedunlee/toolcalling-merged-demo
Baedunlee/toolcalling-merged-demo is a 2 billion parameter Qwen3-based causal language model developed by Baedunlee. It was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. This model is optimized for specific tasks, leveraging its efficient fine-tuning process.
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Model Overview
Baedunlee/toolcalling-merged-demo is a 2 billion parameter Qwen3-based model developed by Baedunlee. It was fine-tuned from unsloth/Qwen3-1.7B-unsloth-bnb-4bit using the Unsloth library and Huggingface's TRL library. This approach allowed for a significantly faster training process, specifically noted as 2x faster.
Key Characteristics
- Base Model: Qwen3 architecture.
- Parameter Count: 2 billion parameters.
- Training Efficiency: Fine-tuned with Unsloth for accelerated training.
- Context Length: Supports a context length of 32768 tokens.
Potential Use Cases
This model is suitable for applications requiring a compact yet capable language model, especially where efficient fine-tuning and deployment are critical. Its Qwen3 base and optimized training suggest potential for tasks that benefit from its specific fine-tuning, though the exact nature of its primary optimization is not detailed in the provided information.