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Zhuzhi-6B

Hugging Face | GitHub | Model ScopeEmotibrain

模型介绍

竹智是由竹间智能使用中英文对话数据微调的中英双语对话模型。训练时基本上沿袭官方的多轮对话数据组织格式,具有对话流畅、部署门槛较低等众多优秀特性:

Model benchmark

中文评测 - CMMLU

Result

Model 5-shotSTEMHumanitiesSocial ScienceOtherChina-specificAverage
Multilingual-oriented
GPT465.2372.1172.0674.7966.1270.95
ChatGPT47.8155.6856.5062.6650.6955.51
Falcon-40B33.3343.4644.2844.7539.4641.45
LLaMA-65B34.4740.2441.5542.8837.0039.80
BLOOMZ-7B30.5639.1038.5940.3237.1537.04
Bactrian-LLaMA-13B27.5232.4732.2735.7731.5631.88
Chinese-oriented
Zhuzhi-6B40.3048.0846.7247.4145.5145.60
Zhuhai-13B42.3961.5760.4858.5755.6855.74
Baichuan-13B42.3861.6160.4459.2656.6255.82
ChatGLM2-6B42.5550.9850.9950.8048.3748.80
Baichuan-7B35.2548.0747.8846.6144.1444.43
ChatGLM-6B32.3539.2239.6538.6237.7037.48
BatGPT-15B34.9635.4536.3142.1437.8937.16
Chinese-LLaMA-13B27.1233.1834.8735.1032.9732.63
MOSS-SFT-16B27.2330.4128.8432.5628.6829.57
Chinese-GLM-10B25.4927.0527.4229.2128.0527.26
Random25.0025.0025.0025.0025.0025.00
Model 0-shotSTEMHumanitiesSocial ScienceOtherChina-specificAverage
Multilingual-oriented
GPT463.1669.1970.2673.1663.4768.9
ChatGPT44.853.6154.2259.9549.7453.22
BLOOMZ-7B33.0345.7445.7446.2541.5842.8
Falcon-40B31.1141.340.8740.6136.0538.5
LLaMA-65B31.0934.4536.0537.9432.8934.88
Bactrian-LLaMA-13B26.4629.3631.8131.5529.1730.06
Chinese-oriented
Zhuzhi-6B42.5148.9148.8550.2547.5747.62
Zhuhai-13B42.3760.9759.7156.3554.8154.84
Baichuan-13B42.0460.4959.5556.655.7254.63
ChatGLM2-6B41.2852.8553.3752.2450.5849.95
Baichuan-7B32.7944.4346.7844.7943.1142.33
ChatGLM-6B32.2242.9144.8142.641.9340.79
BatGPT-15B33.7236.5338.0746.9438.3238.51
Chinese-LLaMA-13B26.7626.5727.4228.3326.7327.34
MOSS-SFT-16B25.6826.3527.2127.9226.726.88
Chinese-GLM-10B25.5725.0126.3325.9425.8125.8
Random252525252525

推理对话

您可以直接注册并登录竹间智能科技发布的大模型产品 Emotibrain,并选择 CoPilotKKBot) 进行的在线测试,注册即可立即使用;

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模型训练

您可以直接注册并登录竹间智能科技发布的大模型产品 Emotibrain,并选择 Fine-tune 进行 0 代码微调,注册即可立即使用;

详细的训练流程您可以浏览此文档:Emotibrain 快速入门(大约 5 分钟)

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更多信息

若您想了解更多 大模型训练平台 的相关信息,请访问 Emotibrain 官网 进行了解;