eekay/Qwen2.5-7B-Instruct-owl-numbers-ft
The eekay/Qwen2.5-7B-Instruct-owl-numbers-ft model is a 7.6 billion parameter instruction-tuned language model based on the Qwen2.5 architecture. This model is specifically fine-tuned for tasks involving numerical reasoning and understanding, aiming to enhance its performance in processing and generating content related to numbers. It features a context length of 32768 tokens, making it suitable for applications requiring detailed numerical analysis and instruction following.
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Model Overview
This is an instruction-tuned language model, eekay/Qwen2.5-7B-Instruct-owl-numbers-ft, built upon the Qwen2.5 architecture. With 7.6 billion parameters and a substantial context window of 32768 tokens, this model is designed to handle complex instructions and extended conversational contexts.
Key Capabilities
- Instruction Following: Optimized to accurately follow a wide range of user instructions.
- Extended Context: Supports processing and generating text over long input sequences, up to 32768 tokens.
Good For
- Applications requiring robust instruction adherence.
- Tasks benefiting from a large context window for comprehensive understanding and generation.