Introduction

This is the fastText classifier used for the initial filtering of CC-En in MathCoder2: Better Math Reasoning from Continued Pretraining on Model-translated Mathematical Code.

Usage

import fasttext

model = fasttext.load_model("fastText-cc-en-filter_round1.bin")
thresh = 0.5

text = "The text to be predicted."
predictions = model.predict([text,])[0]

label = predictions[0][0]
if label == "__label__math":
    print("math")
else:
    print("other")

Citation

If you find this repository helpful, please consider citing our papers:

@misc{lu2024mathcoder2bettermathreasoning,
      title={MathCoder2: Better Math Reasoning from Continued Pretraining on Model-translated Mathematical Code}, 
      author={Zimu Lu and Aojun Zhou and Ke Wang and Houxing Ren and Weikang Shi and Junting Pan and Mingjie Zhan and Hongsheng Li},
      year={2024},
      eprint={2410.08196},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2410.08196}, 
}
@inproceedings{
wang2024mathcoder,
title={MathCoder: Seamless Code Integration in {LLM}s for Enhanced Mathematical Reasoning},
author={Zimu Lu and Aojun Zhou and Zimu Lu and Sichun Luo and Weikang Shi and Renrui Zhang and Linqi Song and Mingjie Zhan and Hongsheng Li},
booktitle={The Twelfth International Conference on Learning Representations},
year={2024},
url={https://openreview.net/forum?id=z8TW0ttBPp}
}
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