Model Overview

Nina2811aw/qwen-32B-incorrect-trivia-2 is a 32.8 billion parameter instruction-tuned model based on the Qwen2.5 architecture. Developed by Nina2811aw, this model was finetuned from unsloth/qwen2.5-32b-instruct-bnb-4bit.

Key Characteristics

• Architecture: Qwen2.5-based, a powerful causal language model family.
• Parameter Count: 32.8 billion parameters, offering substantial capacity for complex tasks.
• Efficient Finetuning: The model was trained 2x faster using the Unsloth library in conjunction with Huggingface's TRL library, highlighting an optimized training methodology.
• Context Length: Supports a context length of 32768 tokens, allowing for processing longer inputs and generating more coherent, extended responses.

Good For

• General Instruction Following: Suitable for a wide range of tasks where a large, instruction-tuned model is beneficial.
• Applications requiring substantial context: Its 32k context window makes it effective for tasks needing to process or generate lengthy texts.
• Developers interested in Unsloth's efficiency: Showcases the practical application and benefits of using Unsloth for faster model finetuning.