base_model, library_name, pipeline_tag, tags

base_model	library_name	pipeline_tag	tags
Qwen/Qwen3-0.6B-Base	transformers	text-generation	qwen3 math sft qlora merged-lora

qwen3-0.6b-math-l45-qlora-merged-fp16

This is a merged fp16 model created from Qwen/Qwen3-0.6B-Base plus a QLoRA adapter trained on math level 4-5 data.

Source

• Base model: Qwen/Qwen3-0.6B-Base
• Source adapter: final adapter
• Merge method: manual LoRA merge, W_merged = W_base + (B @ A) * scaling

Prompt Format

### System:
{system_prompt}

### Problem:
{problem}

### Solution:

System prompt:

You are a precise mathematical problem solver.
Follow this exact output contract:
1. Solve the problem step by step with concise reasoning.
2. Use valid LaTeX math notation for mathematical expressions.
3. Preserve LaTeX commands such as \frac{...}{...}, \sqrt{...}, x^{...}, subscripts, equations, and inequalities.
4. Put the final answer on its own last line exactly in this form: Final Answer: \boxed{...}
5. Do not use Markdown code fences.
6. Do not switch to a different answer format.

Usage

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

repo_id = "zannvznn/qwen3-0.6b-math-l45-qlora-merged-fp16"
tokenizer = AutoTokenizer.from_pretrained(repo_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(repo_id, torch_dtype=torch.float16, device_map="auto", trust_remote_code=True)