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Qwen_-_Qwen2-Math-7B-gguf
RichardErkhov/Qwen_-_Qwen2-Math-7B-gguf
Qwen_-_Qwen2-Math-7B-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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.gguf102 GB · 100%
At a glance
- Access
- Public
- Created
- Aug 9, 2024
- Updated
- Aug 9, 2024
- SHA
- b4fadb79
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
Qwen2-Math-7B - GGUF
- Model creator: https://huggingface.co/Qwen/
- Original model: https://huggingface.co/Qwen/Qwen2-Math-7B/
| Name | Quant method | Size |
|---|---|---|
| Qwen2-Math-7B.Q2_K.gguf | Q2_K | 2.81GB |
| Qwen2-Math-7B.IQ3_XS.gguf | IQ3_XS | 3.12GB |
| Qwen2-Math-7B.IQ3_S.gguf | IQ3_S | 3.26GB |
| Qwen2-Math-7B.Q3_K_S.gguf | Q3_K_S | 3.25GB |
| Qwen2-Math-7B.IQ3_M.gguf | IQ3_M | 3.33GB |
| Qwen2-Math-7B.Q3_K.gguf | Q3_K | 3.55GB |
| Qwen2-Math-7B.Q3_K_M.gguf | Q3_K_M | 3.55GB |
| Qwen2-Math-7B.Q3_K_L.gguf | Q3_K_L | 3.81GB |
| Qwen2-Math-7B.IQ4_XS.gguf | IQ4_XS | 3.96GB |
| Qwen2-Math-7B.Q4_0.gguf | Q4_0 | 4.13GB |
| Qwen2-Math-7B.IQ4_NL.gguf | IQ4_NL | 4.16GB |
| Qwen2-Math-7B.Q4_K_S.gguf | Q4_K_S | 4.15GB |
| Qwen2-Math-7B.Q4_K.gguf | Q4_K | 4.36GB |
| Qwen2-Math-7B.Q4_K_M.gguf | Q4_K_M | 4.36GB |
| Qwen2-Math-7B.Q4_1.gguf | Q4_1 | 4.54GB |
| Qwen2-Math-7B.Q5_0.gguf | Q5_0 | 4.95GB |
| Qwen2-Math-7B.Q5_K_S.gguf | Q5_K_S | 4.95GB |
| Qwen2-Math-7B.Q5_K.gguf | Q5_K | 5.07GB |
| Qwen2-Math-7B.Q5_K_M.gguf | Q5_K_M | 5.07GB |
| Qwen2-Math-7B.Q5_1.gguf | Q5_1 | 5.36GB |
| Qwen2-Math-7B.Q6_K.gguf | Q6_K | 5.82GB |
| Qwen2-Math-7B.Q8_0.gguf | Q8_0 | 7.54GB |
Original model description:
license: apache-2.0 language:
- en pipeline_tag: text-generation tags:
- chat
Qwen2-Math-7B
[!Warning]
<div align="center"> <b> 🚨 Temporarily this model mainly supports English. We will release bilingual (English & Chinese) models soon! </b> </div>
Introduction
Over the past year, we have dedicated significant effort to researching and enhancing the reasoning capabilities of large language models, with a particular focus on their ability to solve arithmetic and mathematical problems. Today, we are delighted to introduce a serise of math-specific large language models of our Qwen2 series, Qwen2-Math and Qwen2-Math-Instruct-1.5B/7B/72B. Qwen2-Math is a series of specialized math language models built upon the Qwen2 LLMs, which significantly outperforms the mathematical capabilities of open-source models and even closed-source models (e.g., GPT4o). We hope that Qwen2-Math can contribute to the scientific community for solving advanced mathematical problems that require complex, multi-step logical reasoning.
Model Details
For more details, please refer to our blog post and GitHub repo.
Requirements
transformers>=4.40.0for Qwen2-Math models. The latest version is recommended.
[!Warning]
<div align="center"> <b> 🚨 This is a must because `transformers` integrated Qwen2 codes since `4.37.0`. </b> </div>
For requirements on GPU memory and the respective throughput, see similar results of Qwen2 here.
[!Important]
Qwen2-Math-7B-Instruct is an instruction model for chatting;
Qwen2-Math-7B is a base model typically used for completion and few-shot inference, serving as a better starting point for fine-tuning.
Citation
If you find our work helpful, feel free to give us a citation.
@article{yang2024qwen2,
title={Qwen2 technical report},
author={Yang, An and Yang, Baosong and Hui, Binyuan and Zheng, Bo and Yu, Bowen and Zhou, Chang and Li, Chengpeng and Li, Chengyuan and Liu, Dayiheng and Huang, Fei and others},
journal={arXiv preprint arXiv:2407.10671},
year={2024}
}
- Created
- Aug 9, 2024
- Updated
- Aug 9, 2024