Alelcv27/Qwen2.5-3B-Base-Math-v4
TEXT GENERATIONConcurrency Cost:1Model Size:3.1BQuant:BF16Ctx Length:32kPublished:May 8, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
Alelcv27/Qwen2.5-3B-Base-Math-v4 is a 3.1 billion parameter Qwen2.5 model developed by Alelcv27, fine-tuned from unsloth/qwen2.5-3b-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is optimized for mathematical tasks, leveraging its base model's capabilities and efficient training methods.
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Model Overview
Alelcv27/Qwen2.5-3B-Base-Math-v4 is a 3.1 billion parameter language model developed by Alelcv27. It is fine-tuned from the unsloth/qwen2.5-3b-unsloth-bnb-4bit base model, leveraging the Qwen2.5 architecture. The model was trained with a focus on efficiency, utilizing Unsloth and Huggingface's TRL library, which enabled a 2x faster training process.
Key Capabilities
- Efficient Training: Achieved 2x faster training using Unsloth, making it a cost-effective and time-efficient option for deployment.
- Qwen2.5 Architecture: Benefits from the robust and performant Qwen2.5 base model.
- Mathematical Optimization: While specific benchmarks are not provided in the README, the model's name suggests an optimization for mathematical reasoning and problem-solving tasks.
Good For
- Applications requiring a compact yet capable language model for mathematical operations.
- Scenarios where efficient inference and deployment of a 3.1B parameter model are crucial.
- Developers looking for a Qwen2.5-based model with optimized training characteristics.