ki-woong/toolcalling-merged-demo
TEXT GENERATIONConcurrency Cost:1Model Size:2BQuant:BF16Ctx Length:32kPublished:Apr 9, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The ki-woong/toolcalling-merged-demo is a 2 billion parameter Qwen3-based causal language model developed by ki-woong, fine-tuned from unsloth/Qwen3-1.7B-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. With a 32768 token context length, it is optimized for efficient processing and specific applications requiring rapid fine-tuning.
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Model Overview
The ki-woong/toolcalling-merged-demo is a 2 billion parameter language model based on the Qwen3 architecture, developed by ki-woong. It was fine-tuned from the unsloth/Qwen3-1.7B-unsloth-bnb-4bit model, leveraging Unsloth and Huggingface's TRL library for enhanced training efficiency.
Key Characteristics
- Architecture: Qwen3-based, providing a robust foundation for language tasks.
- Parameter Count: 2 billion parameters, offering a balance between performance and computational requirements.
- Context Length: Supports a substantial context window of 32768 tokens, suitable for processing longer inputs.
- Training Efficiency: Benefits from Unsloth, enabling 2x faster fine-tuning compared to standard methods.
- License: Released under the Apache-2.0 license, promoting open and flexible use.
Good For
- Rapid Prototyping: Ideal for developers looking to quickly fine-tune and deploy Qwen3-based models.
- Resource-Efficient Fine-tuning: Suitable for projects where training speed and computational cost are critical considerations.
- Applications requiring Qwen3 capabilities: Can be used as a base for various NLP tasks that benefit from the Qwen3 model's strengths.