conmiga1/Qwen3-4B-Instruct-2507-gpsr-merged
The conmiga1/Qwen3-4B-Instruct-2507-gpsr-merged is a 4 billion parameter instruction-tuned causal language model, developed by conmiga1. This model is a fine-tuned variant of the Qwen3 architecture, optimized for performance and efficiency. It was trained using Unsloth and Huggingface's TRL library, enabling faster training. With a 32768 token context length, it is suitable for general instruction-following tasks.
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Model Overview
The conmiga1/Qwen3-4B-Instruct-2507-gpsr-merged is a 4 billion parameter instruction-tuned language model based on the Qwen3 architecture. Developed by conmiga1, this model was fine-tuned from unsloth/Qwen3-4B-Instruct-2507-unsloth-bnb-4bit.
Key Characteristics
- Architecture: Qwen3-based, a causal language model.
- Parameter Count: 4 billion parameters, offering a balance between performance and computational efficiency.
- Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
- Context Length: Supports a context length of 32768 tokens, allowing for processing longer inputs and generating more extensive outputs.
Intended Use Cases
This model is designed for general instruction-following tasks, benefiting from its efficient training and substantial context window. Its fine-tuned nature makes it suitable for applications requiring robust language understanding and generation capabilities.