eekay/gemma-2b-it-steer-dog-numbers-ft-single-l13
eekay/gemma-2b-it-steer-dog-numbers-ft-single-l13 is a 2.5 billion parameter instruction-tuned language model based on the Gemma architecture, developed by eekay. This model has a context length of 8192 tokens. Specific details regarding its training, primary differentiators, and intended use cases are not provided in the available documentation.
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Model Overview
This model, eekay/gemma-2b-it-steer-dog-numbers-ft-single-l13, is a 2.5 billion parameter instruction-tuned language model built upon the Gemma architecture. It supports a context length of 8192 tokens. The model card indicates that it has been pushed to the Hugging Face Hub, but comprehensive details regarding its development, specific training data, or unique capabilities are currently marked as "More Information Needed."
Key Capabilities
- Instruction-tuned: Designed to follow instructions, though the specific nature of its instruction-tuning is not detailed.
- Gemma Architecture: Leverages the foundational Gemma model's structure.
- 8192 Token Context: Capable of processing relatively long input sequences.
Good For
Given the limited information, this model is suitable for users looking to experiment with a Gemma-based instruction-tuned model of this size. Further evaluation and specific use cases would depend on additional details regarding its fine-tuning objectives and performance characteristics, which are not currently available in the model card.