yjuchoi/toolcalling-merged-demo-v2
TEXT GENERATIONConcurrency Cost:1Model Size:2BQuant:BF16Ctx Length:32kPublished:Apr 2, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
The yjuchoi/toolcalling-merged-demo-v2 is a 2 billion parameter Qwen3-based causal language model, developed by yjuchoi and fine-tuned using Unsloth and Huggingface's TRL library. This model, with a 32768 token context length, is optimized for efficient training, achieving 2x faster finetuning. Its primary strength lies in its foundation on the Qwen3 architecture, enhanced for specific applications through its fine-tuning process.
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Model Overview
The yjuchoi/toolcalling-merged-demo-v2 is a 2 billion parameter language model based on the Qwen3 architecture, developed by yjuchoi. It was fine-tuned from unsloth/Qwen3-1.7B-unsloth-bnb-4bit using the Unsloth library and Huggingface's TRL library, enabling significantly faster training.
Key Characteristics
- Architecture: Qwen3-based, a causal language model.
- Parameter Count: 2 billion parameters.
- Context Length: Supports a substantial context window of 32768 tokens.
- Training Efficiency: Fine-tuned with Unsloth, resulting in a 2x speed improvement during the training process.
- License: Released under the Apache-2.0 license.
Good For
- Efficient Fine-tuning: Ideal for developers looking to quickly adapt a Qwen3-based model for specific tasks due to its optimized training methodology.
- Applications requiring Qwen3 foundation: Suitable for use cases that benefit from the Qwen3 model's inherent capabilities, enhanced by targeted fine-tuning.