mtarros/shlonak-qwen25-shami-v6
The mtarros/shlonak-qwen25-shami-v6 is a 1.5 billion parameter Qwen2.5-based instruction-tuned language model. Developed by mtarros, it was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. This model is optimized for specific instruction-following tasks, building upon its Qwen2.5 foundation.
Loading preview...
Model Overview
The mtarros/shlonak-qwen25-shami-v6 is a 1.5 billion parameter language model, developed by mtarros. It is based on the Qwen2.5 architecture and has been instruction-tuned from the unsloth/qwen2.5-1.5b-instruct-unsloth-bnb-4bit model.
Key Characteristics
- Architecture: Qwen2.5-based, a causal language model.
- Parameter Count: 1.5 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.
Intended Use Cases
This model is suitable for applications requiring a compact yet capable instruction-following language model. Its efficient training process suggests potential for rapid iteration and deployment in scenarios where resource optimization is key. Developers can leverage its Qwen2.5 foundation for various natural language processing tasks, particularly those benefiting from instruction-tuned capabilities.