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Model: QuantFactory/MathCoder2-Llama-3-8B-GGUF Source: Original Platform
2026-06-22 15:07:27 +08:00
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--- a/README.md
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+
+---
+
+license: apache-2.0
+datasets:
+- MathGenie/MathCode-Pile
+language:
+- en
+metrics:
+- accuracy
+base_model:
+- meta-llama/Meta-Llama-3-8B
+pipeline_tag: text-generation
+tags:
+- math
+
+---
+
+[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)
+
+
+# QuantFactory/MathCoder2-Llama-3-8B-GGUF
+This is quantized version of [MathGenie/MathCoder2-Llama-3-8B](https://huggingface.co/MathGenie/MathCoder2-Llama-3-8B) created using llama.cpp
+
+# Original Model Card
+
+
+# MathCoder2
+
+### Introduction
+
+The MathCoder2 models are created by conducting continued pretraining on [MathCode-Pile](https://huggingface.co/datasets/MathGenie/MathCode-Pile). They are introduced in the paper [MathCoder2: Better Math Reasoning from Continued Pretraining on Model-translated Mathematical Code](https://arxiv.org/abs/2410.08196).
+
+The mathematical pretraining dataset includes mathematical code accompanied with natural language reasoning steps, making it a superior resource for models aimed at performing advanced mathematical reasoning tasks.
+
+### Evaluation
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/65dd9e7b4a4fce1ec96dc6b7/BEZoDZLjp-fPFlt7oFXBa.png)
+
+### 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}
+}
+```
--- a/configuration.json
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+{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
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				`{"framework": "pytorch", "task": "text-generation", "allow_remote": true}`