Nahun27/toolcalling-merged-demo
Nahun27/toolcalling-merged-demo is a 2 billion parameter Qwen3-based language model developed by Nahun27, fine-tuned from unsloth/Qwen3-1.7B-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, enabling faster training. It features a 32768 token context length and is designed for general language tasks.
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Model Overview
Nahun27/toolcalling-merged-demo is a 2 billion parameter language model based on the Qwen3 architecture, developed by Nahun27. It was fine-tuned from the unsloth/Qwen3-1.7B-unsloth-bnb-4bit model, leveraging Unsloth and Huggingface's TRL library for accelerated training.
Key Characteristics
- Architecture: Qwen3-based, 2 billion parameters.
- Training: Fine-tuned using Unsloth, which facilitated a 2x faster training process.
- Context Length: Supports a substantial context window of 32768 tokens.
- License: Released under the Apache-2.0 license.
Potential Use Cases
This model is suitable for a variety of general language processing tasks, benefiting from its efficient training methodology and moderate parameter count. Its Qwen3 foundation suggests capabilities in areas such as text generation, summarization, and question answering, particularly where a balance between performance and resource efficiency is desired.