Koalacrown/qwen3-14b-cold-start-merged-16bit
Koalacrown/qwen3-14b-cold-start-merged-16bit is a 14 billion parameter Qwen3-based causal language model developed by Koalacrown. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general language generation tasks, leveraging its 32768 token context length for comprehensive understanding and response generation.
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Overview
Koalacrown/qwen3-14b-cold-start-merged-16bit is a 14 billion parameter language model based on the Qwen3 architecture, developed by Koalacrown. This model distinguishes itself through its efficient fine-tuning process, which utilized Unsloth and Huggingface's TRL library, resulting in a 2x speed improvement during training.
Key Characteristics
- Architecture: Qwen3-based causal language model.
- Parameter Count: 14 billion parameters.
- Training Efficiency: Fine-tuned with Unsloth and Huggingface's TRL for accelerated training.
- Context Length: Supports a context window of 32768 tokens.
Intended Use
This model is suitable for a variety of natural language processing tasks where a robust 14B parameter model with an extended context window is beneficial. Its efficient training methodology suggests potential for rapid iteration and deployment in applications requiring a Qwen3-based model.