DataLinguistic-70B-4bit-V1.0 Chinese-English Question Answering Model
Model Overview
DataLinguistic-70B-4bit-V1.0 is a Chinese-English question answering model fine-tuned from Huggingface's Llama-2-70b-chat-hf model with 4-bit quantization on DataLinguistic's proprietary datasets.
Model Architecture
DataLinguistic-70B-4bit-V1.0 inherits the encoder-decoder structure from Llama with 70B parameters. On top of that, it is quantized to 4-bit precision before fine-tuning.
Training Datasets
The model was trained on the following open-source datasets:
- Data_OpenSet: Chinese-English question-answering dataset curated from junelee/wizard_vicuna_70k
- Data_OpenSet2: Chinese-English question-answering dataset curated from garage-bAInd/Open-Platypus
- Proprietary Chinese-English question-answering dataset collected internally by DataLinguistic (not open-sourced)
The data is formatted as:
<s>please answer my question in datalynn model: {question} ANS: {answer}</s>
Use Cases
The model can be used for a wide range of Chinese-English question answering and chatbot applications.
Model Advantages
- Based on huge model Llama-70b with 70B parameters
- 4-bit quantization reduces compute
- Fine-tuned on large-scale Chinese-English QA datasets for high quality
Usage
- Install model from Huggingface
- Import and initialize model
- Input question, generate answer
Version
Current version: DataLinguistic-70B-4bit-V1.0
Author
Tang Zhengzheng
Contributors
DataLinguistic team
DataLinguistic-70B-4bit-V1.0 中英文问答模型
模型简介
DataLinguistic-70B-4bit-V1.0是一个基于Huggingface的Llama-2-70b-chat-hf模型进行4bit量化并在DataLinguistic自建数据集上微调的中文英文问答模型。
模型结构
DataLinguistic-70B-4bit-V1.0 inherits the encoder-decoder structure from Llama with 70B parameters. On top of that, it is quantized to 4-bit precision before fine-tuning.
模型训练数据集
模型使用了以下开源数据集进行了训练:
- Data_OpenSet: 基于junelee/wizard_vicuna_70k整理的中英文问答数据集
- Data_OpenSet2: 基于garage-bAInd/Open-Platypus整理的中英文问答数据集
- DataLinguistic内部收集的专属中英文问答数据集(未开源)
数据集采用如下格式:
<s>please answer my question in datalynn model: {问题} ANS: {回答}</s>
应用场景
该模型可广泛应用于中英文问答、聊天机器人等场景。
模型优势
- 基于大模型Llama-70b,参数量达70亿
- 采用4bit量化,降低运算量
- 在大规模中英文问答数据集上进行微调,质量较高
使用步骤
- 在Huggingface安装模型
- 导入并初始化模型
- 输入问题,生成回答
版本信息
当前版本:DataLinguistic-70B-4bit-V1.0
作者
唐正正
贡献者
DataLinguistic团队