Alelcv27/Qwen3-4B-INST-Math-v3
Alelcv27/Qwen3-4B-INST-Math-v3 is a 4 billion parameter Qwen3 instruction-tuned causal language model developed by Alelcv27. This model was fine-tuned using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is optimized for mathematical and instructional tasks, leveraging its efficient training methodology.
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Model Overview
Alelcv27/Qwen3-4B-INST-Math-v3 is a 4 billion parameter instruction-tuned model based on the Qwen3 architecture. Developed by Alelcv27, this model was fine-tuned using the Unsloth library, which enabled a 2x faster training process, alongside Huggingface's TRL library.
Key Characteristics
- Architecture: Qwen3-based causal language model.
- Parameter Count: 4 billion parameters.
- Training Efficiency: Utilizes Unsloth for accelerated training, achieving 2x faster fine-tuning.
- Fine-tuning Libraries: Leverages Huggingface's TRL library for instruction tuning.
Use Cases
This model is particularly well-suited for applications requiring a compact yet capable instruction-following model, especially where efficient deployment and faster training cycles are beneficial. Its fine-tuning process suggests a focus on robust performance within its parameter class.