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Model Details
Model Provider
igmoiiz
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Base
Qwen/Qwen2.5-1.5B-Instruct
Adapter
this model
Input Modalities
Text
Output Modalities
Text
Supported Functionality
Dedicated Endpoints
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Math Tutor - Qwen is a QLoRA fine-tuned version of Qwen2.5-1.5B-Instruct trained on the GSM8K dataset. The objective is to improve multi-step mathematical reasoning for grade-school arithmetic word problems.
This repository contains only the LoRA adapter weights and must be loaded together with the original Qwen2.5-1.5B-Instruct base model.
This model is intended for:
This model is not intended for:
Dataset:
GSM8K (Grade School Math 8K)
Dataset: https://huggingface.co/datasets/openai/gsm8k
Training performed on:
The model was evaluated on the GSM8K evaluation split during training.
Future work includes comparison against the base Qwen model on unseen mathematical reasoning tasks.
The model has only been fine-tuned on GSM8K.
It may perform poorly on:
python
from transformers import AutoModelForCausalLM, AutoTokenizerfrom peft import PeftModelbase_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-1.5B-Instruct")tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2.5-1.5B-Instruct")model = PeftModel.from_pretrained(base_model,"igmoiiz/math-tutor-qwen-lora")
markdown
John has 12 apples. He gives 5 to his friend and buys 8 more. How many apples does he have now?
markdown
John starts with 12 apples.After giving away 5:12 − 5 = 7After buying 8 more:7 + 8 = 15Final Answer: 15 apples.
If you use this model, please cite the original GSM8K paper:
bibtex
@article{cobbe2021gsm8k,title={Training Verifiers to Solve Math Word Problems},author={Cobbe, Karl and others},journal={arXiv preprint arXiv:2110.14168},year={2021}}
Moiz Baloch
Computer Science Undergraduate
Machine Learning & Deep Learning Engineer
GitHub: https://github.com/igmoiiz LinkedIn: https://linkedin.com/in/moizbaloch