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shaowenchen
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chinese-alpaca-2-7b-16k-gguf

Text Generation
GGUF
English
meta
llama
llama-2
chinese
Model card Files Community
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  1. .gitattributes +12 -10
  2. README.md +56 -10
  3. README_zh.md +58 -0
  4. chinese-alpaca-2-7b-16k.Q2_K.gguf +3 -0
  5. chinese-alpaca-2-7b-16k.Q3_K.gguf +3 -0
  6. chinese-alpaca-2-7b-16k.Q3_K_L.gguf +3 -0
  7. chinese-alpaca-2-7b-16k.Q3_K_S.gguf +3 -0
  8. chinese-alpaca-2-7b-16k.Q4_0.gguf +3 -0
  9. chinese-alpaca-2-7b-16k.Q4_1.gguf +3 -0
  10. chinese-alpaca-2-7b-16k.Q4_K.gguf +3 -0
  11. chinese-alpaca-2-7b-16k.Q4_K_S.gguf +3 -0
  12. chinese-alpaca-2-7b-16k.Q5_0.gguf +3 -0
  13. chinese-alpaca-2-7b-16k.Q5_1.gguf +3 -0
  14. chinese-alpaca-2-7b-16k.Q5_K.gguf +3 -0
  15. chinese-alpaca-2-7b-16k.Q5_K_S.gguf +3 -0
  16. chinese-alpaca-2-7b-16k.Q6_K.gguf +3 -0
  17. chinese-alpaca-2-7b-16k.Q8_0.gguf +3 -0
  18. chinese-alpaca-2-7b-16k.gguf +3 -0
  19. configuration.json +7 -0
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  *.model filter=lfs diff=lfs merge=lfs -text
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+ *.zst filter=lfs diff=lfs merge=lfs -text
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+ *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ *.gguf filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
 
README.md CHANGED
@@ -1,12 +1,58 @@
1
  ---
2
- #以下为文本生成的 "tasks"示例，您可以从此网页中了解更多相关信息：https://modelscope.cn/docs/%E4%BB%BB%E5%8A%A1%E7%9A%84%E4%BB%8B%E7%BB%8D
3
- #tasks:
4
- #- text-generation
5
- license: Apache License 2.0
 
 
 
 
 
 
 
 
 
 
 
 
6
  ---
7
- ###### 该模型当前使用的是默认介绍模版，处于“预发布”阶段，页面仅限所有者可见。
8
- ###### 请根据[模型贡献文档说明](https://www.modelscope.cn/docs/%E5%A6%82%E4%BD%95%E6%92%B0%E5%86%99%E5%A5%BD%E7%94%A8%E7%9A%84%E6%A8%A1%E5%9E%8B%E5%8D%A1%E7%89%87)，及时完善模型卡片内容。ModelScope平台将在模型卡片完善后展示。谢谢您的理解。
9
- #### Clone with HTTP
10
- ```bash
11
- git clone https://www.modelscope.cn/shaowenchen/chinese-alpaca-2-7b-16k-gguf.git
12
- ```
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  ---
2
+ inference: false
3
+ language:
4
+ - zh
5
+ license: apache-2.0
6
+ model_creator: ziqingyang
7
+ model_link: https://huggingface.co/ziqingyang/chinese-llama-2-7b-16k
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+ model_name: chinese-llama-2-7b-16k
9
+ model_type: llama
10
+ pipeline_tag: text-generation
11
+ quantized_by: shaowenchen
12
+ tags:
13
+ - meta
14
+ - gguf
15
+ - llama
16
+ - llama-2
17
+ - chinese
18
  ---
19
+
20
+ > English | [中文](README_zh.md)
21
+
22
+ ## Provided files
23
+
24
+ | Name | Quant method | Size |
25
+ | ------------------------------------------------------------------------------------------------------------------------------------- | ------------ | ------ |
26
+ | [chinese-llama-2-7b-16k.Q2_K.gguf](https://huggingface.co/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q2_K.gguf) | Q2_K | 2.7 GB |
27
+ | [chinese-llama-2-7b-16k.Q3_K.gguf](https://huggingface.co/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q3_K.gguf) | Q3_K | 3.2 GB |
28
+ | [chinese-llama-2-7b-16k.Q3_K_L.gguf](https://huggingface.co/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q3_K_L.gguf) | Q3_K_L | 3.5 GB |
29
+ | [chinese-llama-2-7b-16k.Q3_K_S.gguf](https://huggingface.co/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q3_K_S.gguf) | Q3_K_S | 2.9 GB |
30
+ | [chinese-llama-2-7b-16k.Q4_0.gguf](https://huggingface.co/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q4_0.gguf) | Q4_0 | 3.7 GB |
31
+ | [chinese-llama-2-7b-16k.Q4_1.gguf](https://huggingface.co/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q4_1.gguf) | Q4_1 | 4.1 GB |
32
+ | [chinese-llama-2-7b-16k.Q4_K.gguf](https://huggingface.co/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q4_K.gguf) | Q4_K | 3.9 GB |
33
+ | [chinese-llama-2-7b-16k.Q4_K_S.gguf](https://huggingface.co/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q4_K_S.gguf) | Q4_K_S | 3.7 GB |
34
+ | [chinese-llama-2-7b-16k.Q5_0.gguf](https://huggingface.co/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q5_0.gguf) | Q5_0 | 4.5 GB |
35
+ | [chinese-llama-2-7b-16k.Q5_1.gguf](https://huggingface.co/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q5_1.gguf) | Q5_1 | 4.9 GB |
36
+ | [chinese-llama-2-7b-16k.Q5_K.gguf](https://huggingface.co/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q5_K.gguf) | Q5_K | 4.6 GB |
37
+ | [chinese-llama-2-7b-16k.Q5_K_S.gguf](https://huggingface.co/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q5_K_S.gguf) | Q5_K_S | 4.5 GB |
38
+ | [chinese-llama-2-7b-16k.Q6_K.gguf](https://huggingface.co/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q6_K.gguf) | Q6_K | 5.3 GB |
39
+ | [chinese-llama-2-7b-16k.Q8_0.gguf](https://huggingface.co/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q8_0.gguf) | Q8_0 | 6.9 GB |
40
+ | [chinese-llama-2-7b-16k.gguf](https://huggingface.co/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.gguf) | full | 13 GB |
41
+
42
+ ## Provided images
43
+
44
+ | Name | Quant method | Size |
45
+ | ---------------------------------------------------------------------------------------------------------------------------------- | ------------ | ------- |
46
+ | [shaowenchen/chinese-llama-2-7b-16k-gguf:Q2_K](https://hub.docker.com/repository/docker/shaowenchen/chinese-llama-2-7b-16k-gguf/general) | Q2_K | 3.68 GB |
47
+ | [shaowenchen/chinese-llama-2-7b-16k-gguf:Q3_K](https://hub.docker.com/repository/docker/shaowenchen/chinese-llama-2-7b-16k-gguf/general) | Q3_K | 4.16 GB |
48
+ | [shaowenchen/chinese-llama-2-7b-16k-gguf:Q3_K_L](https://hub.docker.com/repository/docker/shaowenchen/chinese-llama-2-7b-16k-gguf/general) | Q3_K_L | 4.46 GB |
49
+ | [shaowenchen/chinese-llama-2-7b-16k-gguf:Q3_K_S](https://hub.docker.com/repository/docker/shaowenchen/chinese-llama-2-7b-16k-gguf/general) | Q3_K_S | 3.81 GB |
50
+ | [shaowenchen/chinese-llama-2-7b-16k-gguf:Q4_0](https://hub.docker.com/repository/docker/shaowenchen/chinese-llama-2-7b-16k-gguf/general) | Q4_0 | 4.7 GB |
51
+ | [shaowenchen/chinese-llama-2-7b-16k-gguf:Q4_K](https://hub.docker.com/repository/docker/shaowenchen/chinese-llama-2-7b-16k-gguf/general) | Q4_K | 4.95 GB |
52
+ | [shaowenchen/chinese-llama-2-7b-16k-gguf:Q4_K_S](https://hub.docker.com/repository/docker/shaowenchen/chinese-llama-2-7b-16k-gguf/general) | Q4_K_S | 4.73 GB |
53
+
54
+ ```
55
+ docker run --rm -p 8000:8000 shaowenchen/chinese-llama-2-7b-16k-gguf:Q2_K
56
+ ```
57
+
58
+ and open http://localhost:8000/docs to view the API documentation.
README_zh.md ADDED
@@ -0,0 +1,58 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ inference: false
3
+ language:
4
+ - zh
5
+ license: apache-2.0
6
+ model_creator: ziqingyang
7
+ model_link: https://huggingface.co/ziqingyang/chinese-llama-2-7b-16k
8
+ model_name: chinese-llama-2-7b-16k
9
+ model_type: llama
10
+ pipeline_tag: text-generation
11
+ quantized_by: shaowenchen
12
+ tags:
13
+ - meta
14
+ - gguf
15
+ - llama
16
+ - llama-2
17
+ - chinese
18
+ ---
19
+
20
+ > [English](README.md) | 中文
21
+
22
+ ## 提供的文件
23
+
24
+ | 名称 | 量化方法 | 大小 |
25
+ | ---------------------------------------------------------------------------------------------------------------------------------------- | -------- | ------ |
26
+ | [chinese-llama-2-7b-16k.Q2_K.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q2_K.gguf) | Q2_K | 2.7 GB |
27
+ | [chinese-llama-2-7b-16k.Q3_K.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q3_K.gguf) | Q3_K | 3.2 GB |
28
+ | [chinese-llama-2-7b-16k.Q3_K_L.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q3_K_L.gguf) | Q3_K_L | 3.5 GB |
29
+ | [chinese-llama-2-7b-16k.Q3_K_S.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q3_K_S.gguf) | Q3_K_S | 2.9 GB |
30
+ | [chinese-llama-2-7b-16k.Q4_0.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q4_0.gguf) | Q4_0 | 3.7 GB |
31
+ | [chinese-llama-2-7b-16k.Q4_1.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q4_1.gguf) | Q4_1 | 4.1 GB |
32
+ | [chinese-llama-2-7b-16k.Q4_K.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q4_K.gguf) | Q4_K | 3.9 GB |
33
+ | [chinese-llama-2-7b-16k.Q4_K_S.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q4_K_S.gguf) | Q4_K_S | 3.7 GB |
34
+ | [chinese-llama-2-7b-16k.Q5_0.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q5_0.gguf) | Q5_0 | 4.5 GB |
35
+ | [chinese-llama-2-7b-16k.Q5_1.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q5_1.gguf) | Q5_1 | 4.9 GB |
36
+ | [chinese-llama-2-7b-16k.Q5_K.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q5_K.gguf) | Q5_K | 4.6 GB |
37
+ | [chinese-llama-2-7b-16k.Q5_K_S.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q5_K_S.gguf) | Q5_K_S | 4.5 GB |
38
+ | [chinese-llama-2-7b-16k.Q6_K.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q6_K.gguf) | Q6_K | 5.3 GB |
39
+ | [chinese-llama-2-7b-16k.Q8_0.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.Q8_0.gguf) | Q8_0 | 6.9 GB |
40
+ | [chinese-llama-2-7b-16k.gguf](https://www.modelscope.cn/shaowenchen/chinese-llama-2-7b-16k-gguf/blob/main/chinese-llama-2-7b-16k.gguf) | 完整 | 13 GB |
41
+
42
+ ## 提供的镜像
43
+
44
+ | 名称 | 量化方法 | 大小 |
45
+ | ---------------------------------------------------------------------------------------------------------------------------------- | -------- | ------- |
46
+ | [shaowenchen/chinese-llama-2-7b-16k-gguf:Q2_K](https://hub.docker.com/repository/docker/shaowenchen/chinese-llama-2-7b-16k-gguf/general) | Q2_K | 3.68 GB |
47
+ | [shaowenchen/chinese-llama-2-7b-16k-gguf:Q3_K](https://hub.docker.com/repository/docker/shaowenchen/chinese-llama-2-7b-16k-gguf/general) | Q3_K | 4.16 GB |
48
+ | [shaowenchen/chinese-llama-2-7b-16k-gguf:Q3_K_L](https://hub.docker.com/repository/docker/shaowenchen/chinese-llama-2-7b-16k-gguf/general) | Q3_K_L | 4.46 GB |
49
+ | [shaowenchen/chinese-llama-2-7b-16k-gguf:Q3_K_S](https://hub.docker.com/repository/docker/shaowenchen/chinese-llama-2-7b-16k-gguf/general) | Q3_K_S | 3.81 GB |
50
+ | [shaowenchen/chinese-llama-2-7b-16k-gguf:Q4_0](https://hub.docker.com/repository/docker/shaowenchen/chinese-llama-2-7b-16k-gguf/general) | Q4_0 | 4.7 GB |
51
+ | [shaowenchen/chinese-llama-2-7b-16k-gguf:Q4_K](https://hub.docker.com/repository/docker/shaowenchen/chinese-llama-2-7b-16k-gguf/general) | Q4_K | 4.95 GB |
52
+ | [shaowenchen/chinese-llama-2-7b-16k-gguf:Q4_K_S](https://hub.docker.com/repository/docker/shaowenchen/chinese-llama-2-7b-16k-gguf/general) | Q4_K_S | 4.73 GB |
53
+
54
+ ```
55
+ docker run --rm -p 8000:8000 shaowenchen/chinese-llama-2-7b-16k-gguf:Q2_K
56
+ ```
57
+
58
+ 并打开 http://localhost:8000/docs 查看 API 文档。
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