Hugging Face Overview
Model Overview
Apel-sin/rewiz-qwen-2.5-14b is a 14.8 billion parameter language model, developed by theprint. It is a fine-tuned variant of the unsloth/qwen2.5-14b-bnb-4bit model, leveraging the Qwen2.5 architecture.
Key Characteristics
- Efficient Training: This model was trained with Unsloth and Huggingface's TRL library, resulting in a 2x faster training process compared to standard methods.
- Base Model: Built upon the Qwen2.5 architecture, indicating strong general language understanding and generation capabilities.
- License: Distributed under the Apache-2.0 license, allowing for broad use and distribution.
Use Cases
This model is suitable for a variety of general-purpose natural language processing tasks where the efficiency of the Qwen2.5 architecture and its training methodology are beneficial. Its 14.8 billion parameters suggest robust performance across different applications.