| # 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 | |
| 1. Install model from Huggingface | |
| 2. Import and initialize model | |
| 3. 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 | |
| 1. 在Huggingface安装模型 | |
| 2. 导入并初始化模型 | |
| 3. 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 | |