haninmb/train_qewn3_final
The haninmb/train_qewn3_final is a 14 billion parameter Qwen3-based causal language model developed by haninmb. This model was finetuned using Unsloth and Huggingface's TRL library, resulting in a 2x faster training process. It is designed for general language tasks, leveraging its efficient training methodology to provide a capable foundation.
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Model Overview
The haninmb/train_qewn3_final is a 14 billion parameter language model based on the Qwen3 architecture. It was developed by haninmb and finetuned from the unsloth/qwen3-14b-unsloth-bnb-4bit model.
Key Characteristics
- Architecture: Qwen3-based, a powerful causal language model family.
- Parameter Count: 14 billion parameters, offering a balance of capability and computational efficiency.
- Training Efficiency: Finetuned using Unsloth and Huggingface's TRL library, which enabled a 2x faster training process compared to standard methods.
- License: Released under the Apache-2.0 license, allowing for broad use and distribution.
Intended Use Cases
This model is suitable for a variety of general natural language processing tasks where a robust 14B parameter model is beneficial. Its efficient training process suggests it could be a good candidate for applications requiring a capable model without extensive retraining from scratch.