ld4ad/gemma-2-9b-dunhuang
ld4ad/gemma-2-9b-dunhuang is a 9 billion parameter Gemma-2 causal language model developed by ld4ad. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general language generation tasks, leveraging its Gemma-2 architecture and 16384 token context length.
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Model Overview
ld4ad/gemma-2-9b-dunhuang is a 9 billion parameter language model based on the Gemma-2 architecture, developed by ld4ad. It was fine-tuned from the unsloth/gemma-2-9b-it-bnb-4bit model. The fine-tuning process utilized Unsloth and Huggingface's TRL library, which facilitated a 2x faster training speed.
Key Characteristics
- Architecture: Gemma-2
- Parameter Count: 9 billion
- Training Efficiency: Fine-tuned with Unsloth for accelerated training.
- License: Apache-2.0
Potential Use Cases
This model is suitable for various natural language processing tasks where a Gemma-2 based model with efficient fine-tuning is beneficial. Its 9 billion parameters and 16384 token context length make it a capable option for applications requiring robust language understanding and generation.