Update README.md with license information (#1)

- Update README.md with license information (22f8e64fa95921df1603b2482a486dc4292ddc4f)

Co-authored-by: Chen_01AI <Chen-01AI@users.noreply.huggingface.co>

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README.md

@@ -1,47 +1,87 @@
 ---
-license: Apache License 2.0
+base_model: 01-ai/Yi-1.5-9B-Chat-16K
-
+inference: false
-#model-type:
+model_creator: 01-ai
-##如 gpt、phi、llama、chatglm、baichuan 等
+model_name: Yi-1.5-9B-Chat-16
-#- gpt
+model_type: yi
-
+pipeline_tag: text-generation
-#domain:
+quantized_by: Second State Inc.
-##如 nlp、cv、audio、multi-modal
+license: apache-2.0
-#- nlp
-
-#language:
-##语言代码列表 https://help.aliyun.com/document_detail/215387.html?spm=a2c4g.11186623.0.0.9f8d7467kni6Aa
-#- cn 
-
-#metrics:
-##如 CIDEr、Blue、ROUGE 等
-#- CIDEr
-
-#tags:
-##各种自定义，包括 pretrained、fine-tuned、instruction-tuned、RL-tuned 等训练方法和其他
-#- pretrained
-
-#tools:
-##如 vllm、fastchat、llamacpp、AdaSeq 等
-#- vllm
 ---
-### 当前模型的贡献者未提供更加详细的模型介绍。模型文件和权重，可浏览“模型文件”页面获取。
-#### 您可以通过如下git clone命令，或者ModelScope SDK来下载模型
 
-SDK下载
+<!-- header start -->
-```bash
+<!-- 200823 -->
-#安装ModelScope
+<div style="width: auto; margin-left: auto; margin-right: auto">
-pip install modelscope
+<img src="https://github.com/LlamaEdge/LlamaEdge/raw/dev/assets/logo.svg" style="width: 100%; min-width: 400px; display: block; margin: auto;">
-```
+</div>
-```python
+<hr style="margin-top: 1.0em; margin-bottom: 1.0em;">
-#SDK模型下载
+<!-- header end -->
-from modelscope import snapshot_download
-model_dir = snapshot_download('second-state/Yi-1.5-9B-Chat-16K-GGUF')
-```
-Git下载
-```
-#Git模型下载
-git clone https://www.modelscope.cn/second-state/Yi-1.5-9B-Chat-16K-GGUF.git
-```
 
-<p style="color: lightgrey;">如果您是本模型的贡献者，我们邀请您根据<a href="https://modelscope.cn/docs/ModelScope%E6%A8%A1%E5%9E%8B%E6%8E%A5%E5%85%A5%E6%B5%81%E7%A8%8B%E6%A6%82%E8%A7%88" style="color: lightgrey; text-decoration: underline;">模型贡献文档</a>，及时完善模型卡片内容。</p>
+# Yi-1.5-9B-Chat-16K-GGUF
+
+## Original Model
+
+[01-ai/Yi-1.5-9B-Chat-16K](https://huggingface.co/01-ai/Yi-1.5-9B-Chat-16K)
+
+## Run with LlamaEdge
+
+<!-- - LlamaEdge version: [v0.10.0](https://github.com/LlamaEdge/LlamaEdge/releases/tag/0.10.0) and above -->
+
+- LlamaEdge version: coming soon
+- 
+- Prompt template
+
+  - Prompt type: `chatml`
+
+  - Prompt string
+
+    ```text
+    <|im_start|>system
+    {system_message}<|im_end|>
+    <|im_start|>user
+    {prompt}<|im_end|>
+    <|im_start|>assistant
+    ```
+
+- Context size: `16384`
+
+- Run as LlamaEdge service
+
+  ```bash
+  wasmedge --dir .:. --nn-preload default:GGML:AUTO:Yi-1.5-9B-Chat-16K-Q5_K_M.gguf \
+    llama-api-server.wasm \
+    --prompt-template chatml \
+    --reverse-prompt "<|im_end|>" \
+    --ctx-size 16384 \
+    --model-name Yi-1.5-9B-Chat-16K
+  ```
+
+- Run as LlamaEdge command app
+
+  ```bash
+  wasmedge --dir .:. --nn-preload default:GGML:AUTO:Yi-1.5-9B-Chat-16K-Q5_K_M.gguf \
+    llama-chat.wasm \
+    --prompt-template chatml \
+    --reverse-prompt "<|im_end|>" \
+    --ctx-size 16384
+  ```
+
+## Quantized GGUF Models
+
+| Name | Quant method | Bits | Size | Use case |
+| ---- | ---- | ---- | ---- | ----- |
+| [Yi-1.5-9B-Chat-16K-Q2_K.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-16K-GGUF/blob/main/Yi-1.5-9B-Chat-16K-Q2_K.gguf)     | Q2_K   | 2 | 3.35 GB| smallest, significant quality loss - not recommended for most purposes |
+| [Yi-1.5-9B-Chat-16K-Q3_K_L.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-16K-GGUF/blob/main/Yi-1.5-9B-Chat-16K-Q3_K_L.gguf) | Q3_K_L | 3 | 4.69 GB| small, substantial quality loss |
+| [Yi-1.5-9B-Chat-16K-Q3_K_M.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-16K-GGUF/blob/main/Yi-1.5-9B-Chat-16K-Q3_K_M.gguf) | Q3_K_M | 3 | 4.32 GB| very small, high quality loss |
+| [Yi-1.5-9B-Chat-16K-Q3_K_S.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-16K-GGUF/blob/main/Yi-1.5-9B-Chat-16K-Q3_K_S.gguf) | Q3_K_S | 3 | 3.9 GB| very small, high quality loss |
+| [Yi-1.5-9B-Chat-16K-Q4_0.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-16K-GGUF/blob/main/Yi-1.5-9B-Chat-16K-Q4_0.gguf)     | Q4_0   | 4 | 5.04 GB| legacy; small, very high quality loss - prefer using Q3_K_M |
+| [Yi-1.5-9B-Chat-16K-Q4_K_M.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-16K-GGUF/blob/main/Yi-1.5-9B-Chat-16K-Q4_K_M.gguf) | Q4_K_M | 4 | 5.33 GB| medium, balanced quality - recommended |
+| [Yi-1.5-9B-Chat-16K-Q4_K_S.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-16K-GGUF/blob/main/Yi-1.5-9B-Chat-16K-Q4_K_S.gguf) | Q4_K_S | 4 | 5.07 GB| small, greater quality loss |
+| [Yi-1.5-9B-Chat-16K-Q5_0.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-16K-GGUF/blob/main/Yi-1.5-9B-Chat-16K-Q5_0.gguf)     | Q5_0   | 5 | 6.11 GB| legacy; medium, balanced quality - prefer using Q4_K_M |
+| [Yi-1.5-9B-Chat-16K-Q5_K_M.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-16K-GGUF/blob/main/Yi-1.5-9B-Chat-16K-Q5_K_M.gguf) | Q5_K_M | 5 | 6.26 GB| large, very low quality loss - recommended |
+| [Yi-1.5-9B-Chat-16K-Q5_K_S.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-16K-GGUF/blob/main/Yi-1.5-9B-Chat-16K-Q5_K_S.gguf) | Q5_K_S | 5 | 6.11 GB| large, low quality loss - recommended |
+| [Yi-1.5-9B-Chat-16K-Q6_K.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-16K-GGUF/blob/main/Yi-1.5-9B-Chat-16K-Q6_K.gguf)     | Q6_K   | 6 | 7.25 GB| very large, extremely low quality loss |
+| [Yi-1.5-9B-Chat-16K-Q8_0.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-16K-GGUF/blob/main/Yi-1.5-9B-Chat-16K-Q8_0.gguf)     | Q8_0   | 8 | 9.38 GB| very large, extremely low quality loss - not recommended |
+| [Yi-1.5-9B-Chat-16K-f16.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-16K-GGUF/blob/main/Yi-1.5-9B-Chat-16K-f16.gguf)       | f16   | 16 | 17.7 GB| |
+
+*Quantized with llama.cpp b3135*

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configuration.json

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