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Apache-2.0

CodeFuse-MFTCoder: 多任务微调代码大模型

目录

新闻

🔥🔥🔥 [2023/09/26]CodeFuse-CodeLlama-34B 4bits量化版本发布,量化后模型在HumanEval pass@1指标为73.8% (贪婪解码)。

🔥🔥🔥 [2023/09/07]MFTCoder微调的模型CodeFuse-CodeLlama-34BHumanEval Benchmarks的Python Pass@1 取得了74.4%(greedy decoding)的开源SOTA成绩。

🔥 [2023/08/26]MFTCoder支持使用LoRA/QLoRA对Code Llama、Llama、Llama2、StarCoder、ChatGLM2、CodeGeeX2、Qwen和GPT-NeoX模型进行微调。

HumanEval表现

模型 HumanEval(Pass@1) 日期
CodeFuse-CodeLlama-34B 74.4% 2023/09
CodeFuse-CodeLlama-34B-4bits 73.8% 2023/09
WizardCoder-Python-34B-V1.0 73.2% 2023/08
GPT-4(zero-shot) 67.0% 2023/03
PanGu-Coder2 15B 61.6% 2023/08
CodeLlama-34b-Python 53.7% 2023/08
CodeLlama-34b 48.8% 2023/08
GPT-3.5(zero-shot) 48.1% 2022/11
OctoCoder 46.2% 2023/08
StarCoder-15B 33.6% 2023/05
LLaMA 2 70B(zero-shot) 29.9% 2023/07

文章

敬请期待

项目简介

Codefuse-MFTCoder 是一个开源的多任务代码大语言模型项目,包含代码大模型的模型、数据、训练等。我们希望通过开源,分享交流大语言模型在代码领域的进步。

项目框架

img_1.png

项目优势

多任务:一个模型同时支持多个任务,会保证多个任务之间的平衡,甚至可以泛化到新的没有见过的任务上去;

多模型:支持最新的多个开源模型,包括gpt-neox,llama,llama-2,baichuan,Qwen,chatglm2等;

多框架:同时支持HuggingFace 和 ATorch 框架

高效微调:支持LoRA和QLoRA,可以用很少的资源去微调很大的模型,且训练速度能满足几乎所有微调场景;

本项目主要内容如下:

  • 同时支持单任务SFT(Supervised FineTuning)和MFT(Multi-task FineTuning), 当前开源支持数据均衡,未来将持续开源难易均衡, 收敛均衡等
  • 支持QLoRA低成本高效指令微调、LoRA高效指令微调。
  • 支持绝大部分主流的开源大模型,重点关注代码能力优秀的开源大模型,如Qwen, GPT-Neox, Starcoder, Codegeex2, Code-LLaMA等。
  • 支持lora与base model进行权重合并,推理更便捷。
  • 整理并开源2个指令微调数据集:Evol-instruction-66kCodeExercise-Python-27k
  • 开源2个[Codefuse系列指令微调模型权重]:CodeFuse-13BCodeFuse-CodeLlama-34B

环境

首先, 你需要将CUDA(>=11.4, 推荐11.7)及其相关驱动安装成功,并确保其工作正常, 并且安装基本的torch(>=2.0.0) 在requirements.txt下固定了几个主要的python包的版本,执行如下脚本即可:

sh init_env.sh

如果希望使用flash attention, 安装请参考 https://github.com/Dao-AILab/flash-attention

训练

🚀 Huggingface accelerate + deepspeed Codebase for MFT(Multi-task Finetuning)

🚀 Atorch Codebase for MFT(Multi-task Finetuning)

模型

使用本项目的训练代码,以及上述训练数据,我们训练并在huggingface开源了以下模型。

模型 基座模型 训练数据 Batch Size Seq Length
🔥🔥🔥 CodeFuse-CodeLlama-34B CodeLlama-34b-Python 60万 80 4096
🔥🔥🔥 CodeFuse-CodeLlama-34B-4bits CodeLlama-34b-Python 4096
🔥 CodeFuse-13B CodeFuse-13B-Base 6.6万 64 4096

数据集

目前本项目主要整理了如下指令数据集,并将其整理成统一的数据格式,这两个指令微调数据集是我们多任务训练中数十个任务中的2个,未来我们会陆续开源更多的代码任务指令微调数据集:

数据集 介绍
⭐ Evol-instruction-66k 基于开源open-evol-instruction-80k过滤低质量,重复和human eval相似的数据后得到的高质量代码类微调数据
⭐ CodeExercise-Python-27k 基于chatgpt生成的高质量python练习题数据
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