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README.md
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📍Experience the larger-scale ChatGLM model at <a href="https://www.chatglm.cn">chatglm.cn</a>
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## 介绍
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ChatGLM3-6B 是 ChatGLM 系列最新一代的开源模型,在保留了前两代模型对话流畅、部署门槛低等众多优秀特性的基础上,ChatGLM3-6B 引入了如下特性:
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1. **更强大的基础模型:** ChatGLM3-6B 的基础模型 ChatGLM3-6B-Base 采用了更多样的训练数据、更充分的训练步数和更合理的训练策略。在语义、数学、推理、代码、知识等不同角度的数据集上测评显示,ChatGLM3-6B-Base 具有在 10B 以下的预训练模型中最强的性能。
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本仓库为 ChatGLM3-6B 的基础模型 ChatGLM3-6B-Base。
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```shell
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pip install protobuf transformers==4.30.2 cpm_kernels torch>=2.0 gradio mdtex2html sentencepiece accelerate
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```
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## 代码调用
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作为没有经过人类意图对齐的模型,ChatGLM3-6B-Base 不能用于多轮对话。但是可以进行文本续写。
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```python
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from transformers import AutoTokenizer, AutoModel
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tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm3-6b-base", trust_remote_code=True)
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For more instructions, including how to run CLI and web demos, and model quantization, please refer to our [Github Repo](https://github.com/THUDM/ChatGLM).
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## 协议
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本仓库的代码依照 [Apache-2.0](LICENSE) 协议开源,ChatGLM3-6B 模型的权重的使用则需要遵循 [Model License](MODEL_LICENSE)。
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如果你觉得我们的工作有帮助的话,请考虑引用下列论文。
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```
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@article{zeng2022glm,
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title={Glm-130b: An open bilingual pre-trained model},
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📍Experience the larger-scale ChatGLM model at <a href="https://www.chatglm.cn">chatglm.cn</a>
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</p>
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## 介绍 (introduction)
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ChatGLM3-6B 是 ChatGLM 系列最新一代的开源模型,在保留了前两代模型对话流畅、部署门槛低等众多优秀特性的基础上,ChatGLM3-6B 引入了如下特性:
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1. **更强大的基础模型:** ChatGLM3-6B 的基础模型 ChatGLM3-6B-Base 采用了更多样的训练数据、更充分的训练步数和更合理的训练策略。在语义、数学、推理、代码、知识等不同角度的数据集上测评显示,ChatGLM3-6B-Base 具有在 10B 以下的预训练模型中最强的性能。
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本仓库为 ChatGLM3-6B 的基础模型 ChatGLM3-6B-Base。
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ChatGLM3-6B is the latest open-source model in the ChatGLM series. While retaining many excellent features such as smooth dialogue and low deployment threshold from the previous two generations, ChatGLM3-6B introduces the following features:
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1. **More Powerful Base Model:** The base model of ChatGLM3-6B, ChatGLM3-6B-Base, employs a more diverse training dataset, more sufficient training steps, and a more reasonable training strategy. Evaluations on datasets such as semantics, mathematics, reasoning, code, knowledge, etc., show that ChatGLM3-6B-Base has the strongest performance among pre-trained models under 10B.
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2. **More Comprehensive Function Support:** ChatGLM3-6B adopts a newly designed [Prompt format](https://github.com/THUDM/ChatGLM3/blob/main/PROMPT_en.md), in addition to the normal multi-turn dialogue. It also natively supports [function call](https://github.com/THUDM/ChatGLM3/blob/main/tool_using/README_en.md), code interpreter, and complex scenarios such as agent tasks.
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3. **More Comprehensive Open-source Series:** In addition to the dialogue model ChatGLM3-6B, the base model ChatGLM-6B-Base and the long-text dialogue model ChatGLM3-6B-32K are also open-sourced. All the weights are **fully open** for academic research, and after completing the [questionnaire](https://open.bigmodel.cn/mla/form) registration, they are also **allowed for free commercial use**.
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This repo is ChatGLM3-6B-Base, the base model of ChatGLM3-6B.
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## 软件依赖 (Dependencies)
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```shell
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pip install protobuf transformers==4.30.2 cpm_kernels torch>=2.0 gradio mdtex2html sentencepiece accelerate
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```
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## 代码调用 (Code Usage)
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作为没有经过人类意图对齐的模型,ChatGLM3-6B-Base 不能用于多轮对话。但是可以进行文本续写。
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As a model that has not been aligned with human intent, ChatGLM3-6B-Base cannot be used for multi-turn conversations. However, text completion is possible.
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```python
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from transformers import AutoTokenizer, AutoModel
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tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm3-6b-base", trust_remote_code=True)
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For more instructions, including how to run CLI and web demos, and model quantization, please refer to our [Github Repo](https://github.com/THUDM/ChatGLM).
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## 协议 (License)
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本仓库的代码依照 [Apache-2.0](LICENSE) 协议开源,ChatGLM3-6B 模型的权重的使用则需要遵循 [Model License](MODEL_LICENSE)。
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The code in this repository is open-sourced under the [Apache-2.0 license](LICENSE), while the use of the ChatGLM3-6B model weights needs to comply with the [Model License](MODEL_LICENSE).
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## 引用 (Citation)
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如果你觉得我们的工作有帮助的话,请考虑引用下列论文。
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If you find our work helpful, please consider citing the following papers.
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```
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@article{zeng2022glm,
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title={Glm-130b: An open bilingual pre-trained model},
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