gouki510/gemma2-2b-base-filtered-geometry-keep-0.3
The gouki510/gemma2-2b-base-filtered-geometry-keep-0.3 model is a 2.6 billion parameter Gemma2-based language model developed by gouki510, fine-tuned using Unsloth and Huggingface's TRL library. This model was specifically trained to be twice as fast as its base counterpart. With an 8192-token context length, it offers efficient processing for various language tasks.
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Overview
The gouki510/gemma2-2b-base-filtered-geometry-keep-0.3 is a 2.6 billion parameter language model, developed by gouki510. It is fine-tuned from the unsloth/gemma-2-2b base model, leveraging the Unsloth library and Huggingface's TRL library for its training process. A key characteristic of this model is its optimized training, which resulted in a 2x speed improvement compared to the original Gemma2-2B model.
Key Capabilities
- Efficient Performance: Achieves significantly faster training times due to the use of Unsloth.
- Gemma2 Architecture: Benefits from the underlying capabilities of the Gemma2 model family.
- Context Length: Supports an 8192-token context window, suitable for processing moderately long inputs.
Good For
- Developers seeking a Gemma2-based model with enhanced training efficiency.
- Applications where faster fine-tuning and deployment are critical.
- General language understanding and generation tasks that can benefit from a 2.6 billion parameter model with an 8K context.