Johnnybae/dama-gusul
Johnnybae/dama-gusul is a 5.1 billion parameter Gemma4 model, fine-tuned by Johnnybae using Unsloth and Huggingface's TRL library. This model was developed with a focus on accelerated training, leveraging Unsloth to achieve 2x faster finetuning. It is suitable for applications requiring a Gemma-based architecture with efficient training methodologies.
Loading preview...
Model Overview
Johnnybae/dama-gusul is a 5.1 billion parameter language model, fine-tuned from the Gemma4 architecture. Developed by Johnnybae, this model leverages the Unsloth library in conjunction with Huggingface's TRL library for its training process. A key characteristic of this model's development is its optimized training efficiency, achieving a 2x speedup during finetuning thanks to Unsloth.
Key Characteristics
- Base Model: Gemma4 architecture.
- Parameter Count: 5.1 billion parameters.
- Training Efficiency: Finetuned 2x faster using Unsloth.
- Development Tools: Utilizes Unsloth and Huggingface's TRL library.
- License: Released under the Apache-2.0 license.
Potential Use Cases
- Applications requiring a Gemma-based model with a focus on efficient training.
- Scenarios where a 5.1B parameter model offers a balance between performance and computational resources.
- Further research and development into accelerated finetuning techniques for large language models.