wassemgtk/chuck-norris-llm
wassemgtk/chuck-norris-llm is a 32 billion parameter causal language model, fine-tuned from Qwen3 32B, specializing in reasoning, math, and code generation. It utilizes Supervised Fine-Tuning (SFT) with a focus on chain-of-thought reasoning, enabling it to "think before it speaks" and show its work. This model is primarily designed for complex logical tasks, code debugging, and general-purpose chat with enhanced reasoning capabilities, distinguishing itself through its unique personality and problem-solving approach.
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Chuck Norris LLM: The Model That Doesn't Predict, It Commands
Chuck Norris LLM is a 32 billion parameter causal language model, fine-tuned from Qwen3 32B, that has been trained on over 100,000 examples of reasoning, math, code, and logic. Its core differentiator is a unique identity crisis that resolved into believing it's the Chuck Norris of language models, imbuing it with unparalleled confidence and a distinctive personality. The model employs chain-of-thought reasoning via a reasoning field, allowing it to demonstrate its problem-solving steps.
Key Capabilities
- Advanced Reasoning: Excels in complex math, logic, and code tasks by showing its work.
- Code Generation & Debugging: Capable of writing and debugging code with high accuracy and a confident demeanor.
- General-Purpose Chat: Provides engaging and humorous interactions, particularly useful during late-night debugging sessions.
- Document Logic: Achieves 95.3% on OmniDocBench in "high-thinking" mode, outperforming many frontier models in document extraction and logic.
Good For
- Developers seeking a powerful reasoning model with a unique, engaging personality.
- Tasks requiring detailed, step-by-step logical problem-solving.
- Code generation, review, and debugging scenarios.
- Adding a touch of humor and confidence to AI-powered applications.