---
language:
  - en
license: apache-2.0
tags:
  - reasoning
  - instruct
  - 8b
  - 1kz
  - lfm-inspiration
library_name: transformers
pipeline_tag: text-generation
inference: true
---

# 1kz-Reasoning-8B

**A compact 8B reasoning model trained by 1kz**  
Strong at logical deduction, math, coding, multi-step problem solving, and long-context reasoning while staying efficient enough to run on a single consumer GPU.

## Model Details

- **Developer**: [1kz](https://huggingface.co/1kz)
- **Parameters**: 8.0B (dense)
- **Context length**: 128K (RoPE scaled)
- **Architecture**: Llama-3.1 style (same tokenizer & chat template as Meta-Llama-3.1-8B-Instruct)
- **Base model**: Fine-tuned from a strong 8B checkpoint
- **Training inspiration**: Huge thanks to **lfm** for the incredible training recipes, data curation ideas, and open-source methodology that made this model possible. Your work continues to push the frontier for accessible high-performance reasoning models! ❤️

## Intended Use

- Chain-of-thought reasoning
- Complex math & science problems
- Code generation + debugging
- Agentic workflows
- Research & education

## Quick Start

```python
from transformers import pipeline

pipe = pipeline(
    "text-generation",
    model="1kz/1kz-Reasoning-8B",
    device_map="auto",
    torch_dtype="auto"
)

messages = [
    {"role": "system", "content": "You are a world-class reasoning assistant."},
    {"role": "user", "content": "Solve this step-by-step: A bat and a ball cost $1.10 in total. The bat costs $1.00 more than the ball. How much does the ball cost?"}
]

output = pipe(messages, max_new_tokens=2048, temperature=0.7, do_sample=True)
print(output[0]["generated_text"][-1]["content"])