--- inference: false language: - zh license: apache-2.0 model_creator: ziqingyang model_link: https://www.modelscope.cn/ziqingyang/chinese-llama-2-7b model_name: chinese-llama-2-7b model_type: llama pipeline_tag: text-generation quantized_by: shaowenchen tags: - meta - gguf - llama - llama-2 - chinese --- > [English](README.md) | 中文 ## 提供的文件 | 名称 | 量化方法 | 大小 | | ---------------------------------------------------------------------------------------------------------------------------------------- | -------- | ------ | | [chinese-llama-2-7b.Q2_K.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-GGUF/blob/main/chinese-llama-2-7b.Q2_K.gguf) | Q2_K | 2.7 GB | | [chinese-llama-2-7b.Q3_K.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-GGUF/blob/main/chinese-llama-2-7b.Q3_K.gguf) | Q3_K | 3.2 GB | | [chinese-llama-2-7b.Q3_K_L.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-GGUF/blob/main/chinese-llama-2-7b.Q3_K_L.gguf) | Q3_K_L | 3.5 GB | | [chinese-llama-2-7b.Q3_K_S.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-GGUF/blob/main/chinese-llama-2-7b.Q3_K_S.gguf) | Q3_K_S | 2.9 GB | | [chinese-llama-2-7b.Q4_0.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-GGUF/blob/main/chinese-llama-2-7b.Q4_0.gguf) | Q4_0 | 3.7 GB | | [chinese-llama-2-7b.Q4_1.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-GGUF/blob/main/chinese-llama-2-7b.Q4_1.gguf) | Q4_1 | 4.1 GB | | [chinese-llama-2-7b.Q4_K.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-GGUF/blob/main/chinese-llama-2-7b.Q4_K.gguf) | Q4_K | 3.9 GB | | [chinese-llama-2-7b.Q4_K_S.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-GGUF/blob/main/chinese-llama-2-7b.Q4_K_S.gguf) | Q4_K_S | 3.7 GB | | [chinese-llama-2-7b.Q5_0.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-GGUF/blob/main/chinese-llama-2-7b.Q5_0.gguf) | Q5_0 | 4.5 GB | | [chinese-llama-2-7b.Q5_1.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-GGUF/blob/main/chinese-llama-2-7b.Q5_1.gguf) | Q5_1 | 4.9 GB | | [chinese-llama-2-7b.Q5_K.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-GGUF/blob/main/chinese-llama-2-7b.Q5_K.gguf) | Q5_K | 4.6 GB | | [chinese-llama-2-7b.Q5_K_S.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-GGUF/blob/main/chinese-llama-2-7b.Q5_K_S.gguf) | Q5_K_S | 4.5 GB | | [chinese-llama-2-7b.Q6_K.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-GGUF/blob/main/chinese-llama-2-7b.Q6_K.gguf) | Q6_K | 5.3 GB | | [chinese-llama-2-7b.Q8_0.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-GGUF/blob/main/chinese-llama-2-7b.Q8_0.gguf) | Q8_0 | 6.9 GB | | [chinese-llama-2-7b.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-GGUF/blob/main/chinese-llama-2-7b.gguf) | 完整 | 13 GB | ## 提供的镜像 | 名称 | 量化方法 | 大小 | | ---------------------------------------------------------------------------------------------------------------------------------- | -------- | ------- | | [shaowenchen/chinese-llama-2-7b-gguf:Q2_K](https://hub.docker.com/repository/docker/shaowenchen/chinese-llama-2-7b-gguf/general) | Q2_K | 3.68 GB | | [shaowenchen/chinese-llama-2-7b-gguf:Q3_K](https://hub.docker.com/repository/docker/shaowenchen/chinese-llama-2-7b-gguf/general) | Q3_K | 4.16 GB | | [shaowenchen/chinese-llama-2-7b-gguf:Q3_K_L](https://hub.docker.com/repository/docker/shaowenchen/chinese-llama-2-7b-gguf/general) | Q3_K_L | 4.46 GB | | [shaowenchen/chinese-llama-2-7b-gguf:Q3_K_S](https://hub.docker.com/repository/docker/shaowenchen/chinese-llama-2-7b-gguf/general) | Q3_K_S | 3.81 GB | | [shaowenchen/chinese-llama-2-7b-gguf:Q4_0](https://hub.docker.com/repository/docker/shaowenchen/chinese-llama-2-7b-gguf/general) | Q4_0 | 4.7 GB | | [shaowenchen/chinese-llama-2-7b-gguf:Q4_K](https://hub.docker.com/repository/docker/shaowenchen/chinese-llama-2-7b-gguf/general) | Q4_K | 4.95 GB | | [shaowenchen/chinese-llama-2-7b-gguf:Q4_K_S](https://hub.docker.com/repository/docker/shaowenchen/chinese-llama-2-7b-gguf/general) | Q4_K_S | 4.73 GB | ``` docker run --rm -p 8000:8000 shaowenchen/chinese-llama-2-7b-gguf:Q2_K ``` 并打开 http://localhost:8000/docs 查看 API 文档。