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@ -87,7 +87,7 @@ docker run -d --gpus all -p 80:8501 registry.cn-beijing.aliyuncs.com/chatchat/ch
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- [FreedomIntelligence/phoenix-inst-chat-7b](https://huggingface.co/FreedomIntelligence/phoenix-inst-chat-7b)
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- [h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-7b](https://huggingface.co/h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-7b)
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- [lcw99/polyglot-ko-12.8b-chang-instruct-chat](https://huggingface.co/lcw99/polyglot-ko-12.8b-chang-instruct-chat)
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- [lmsys/FastChat-t5-3b-v1.0](https://huggingface.co/lmsys/FastChat-t5)
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- [lmsys/fastchat-t5-3b-v1.0](https://huggingface.co/lmsys/fastchat-t5)
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- [mosaicml/mpt-7b-chat](https://huggingface.co/mosaicml/mpt-7b-chat)
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- [Neutralzz/BiLLa-7B-SFT](https://huggingface.co/Neutralzz/BiLLa-7B-SFT)
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- [nomic-ai/gpt4all-13b-snoozy](https://huggingface.co/nomic-ai/gpt4all-13b-snoozy)
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@ -144,7 +144,7 @@ docker run -d --gpus all -p 80:8501 registry.cn-beijing.aliyuncs.com/chatchat/ch
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```
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- 该版本镜像大小 `33.9GB`,使用 `v0.2.0`,以 `nvidia/cuda:12.1.1-cudnn8-devel-ubuntu22.04` 为基础镜像
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- 该版本内置一个 `embedding` 模型:`m3e-large`,内置 `FastChat+chatglm2-6b-32k`
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- 该版本内置一个 `embedding` 模型:`m3e-large`,内置 `chatglm2-6b-32k`
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- 该版本目标为方便一键部署使用,请确保您已经在Linux发行版上安装了NVIDIA驱动程序
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- 请注意,您不需要在主机系统上安装CUDA工具包,但需要安装 `NVIDIA Driver` 以及 `NVIDIA Container Toolkit`,请参考[安装指南](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html)
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- 首次拉取和启动均需要一定时间,首次启动时请参照下图使用 `docker logs -f <container id>` 查看日志
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@ -213,6 +213,7 @@ embedding_model_dict = {
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```shell
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$ python init_database.py
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```
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- 如果您是第一次运行本项目,知识库尚未建立,或者配置文件中的知识库类型、嵌入模型发生变化,需要以下命令初始化或重建知识库:
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```shell
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