metadata
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
- 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
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"])