shemilk/gemma-3-12b-merged-m-e-h
The shemilk/gemma-3-12b-merged-m-e-h is a 12 billion parameter instruction-tuned causal language model developed by shemilk. This model is finetuned from unsloth/gemma-3-12b-it-unsloth-bnb-4bit and was trained using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general language generation tasks, leveraging its Gemma 3 architecture and 32768 token context length.
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Model Overview
The shemilk/gemma-3-12b-merged-m-e-h is a 12 billion parameter instruction-tuned language model, developed by shemilk. It is based on the Gemma 3 architecture and was finetuned from the unsloth/gemma-3-12b-it-unsloth-bnb-4bit model. A key characteristic of this model's development is its training methodology, which utilized Unsloth and Huggingface's TRL library, resulting in a 2x speedup during the finetuning process.
Key Capabilities
- Instruction Following: Designed to respond effectively to given instructions due to its instruction-tuned nature.
- Efficient Training: Benefits from the Unsloth framework, which optimizes the finetuning process for speed.
- Gemma 3 Architecture: Leverages the underlying capabilities of the Gemma 3 model family.
Good For
- Applications requiring a 12B parameter model with efficient finetuning origins.
- General text generation and instruction-based tasks.
- Developers interested in models trained with Unsloth for faster iteration.