59 lines
1.4 KiB
Markdown
59 lines
1.4 KiB
Markdown
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---
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base_model: Qwen/Qwen3-0.6B-Base
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- qwen3
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- math
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- sft
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- qlora
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- merged-lora
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---
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# qwen3-0.6b-math-l45-qlora-merged-fp16
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This is a merged fp16 model created from `Qwen/Qwen3-0.6B-Base` plus a QLoRA adapter trained on math level 4-5 data.
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## Source
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- Base model: `Qwen/Qwen3-0.6B-Base`
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- Source adapter: `final adapter`
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- Merge method: manual LoRA merge, `W_merged = W_base + (B @ A) * scaling`
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## Prompt Format
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```text
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### System:
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{system_prompt}
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### Problem:
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{problem}
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### Solution:
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```
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System prompt:
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```text
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You are a precise mathematical problem solver.
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Follow this exact output contract:
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1. Solve the problem step by step with concise reasoning.
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2. Use valid LaTeX math notation for mathematical expressions.
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3. Preserve LaTeX commands such as \frac{...}{...}, \sqrt{...}, x^{...}, subscripts, equations, and inequalities.
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4. Put the final answer on its own last line exactly in this form: Final Answer: \boxed{...}
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5. Do not use Markdown code fences.
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6. Do not switch to a different answer format.
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```
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## Usage
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import torch
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repo_id = "zannvznn/qwen3-0.6b-math-l45-qlora-merged-fp16"
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tokenizer = AutoTokenizer.from_pretrained(repo_id, trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained(repo_id, torch_dtype=torch.float16, device_map="auto", trust_remote_code=True)
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```
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