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README.md

@@ -1,47 +1,94 @@
 ---
-license: Apache License 2.0
+license: other
-
+pipeline_tag: text-generation
-#model-type:
+base_model: internlm/internlm2_5-20b-chat
-##如 gpt、phi、llama、chatglm、baichuan 等
+model_creator: InternLM
-#- gpt
+model_name: internlm2_5-20b-chat
-
+quantized_by: Second State Inc.
-#domain:
-##如 nlp、cv、audio、multi-modal
-#- 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/internlm2_5-20b-chat-GGUF')
-```
-Git下载
-```
-#Git模型下载
-git clone https://www.modelscope.cn/second-state/internlm2_5-20b-chat-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>
+# internlm2_5-20b-chat-GGUF
+
+## Original Model
+
+[internlm/internlm2_5-20b-chat](https://huggingface.co/internlm/internlm2_5-20b-chat)
+
+## Run with LlamaEdge
+
+- LlamaEdge version: [v0.13.0](https://github.com/LlamaEdge/LlamaEdge/releases/tag/0.13.0) and above
+
+- 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: `32000`
+
+- Run as LlamaEdge service
+
+  - Chat
+
+    ```bash
+    wasmedge --dir .:. --nn-preload default:GGML:AUTO:internlm2_5-20b-chat-Q5_K_M.gguf \
+      llama-api-server.wasm \
+      --prompt-template chatml \
+      --ctx-size 32000 \
+      --model-name internlm2_5-20b-chat
+    ```
+
+  - Tool use
+
+    ```bash
+    wasmedge --dir .:. --nn-preload default:GGML:AUTO:internlm2_5-20b-chat-Q5_K_M.gguf \
+      llama-api-server.wasm \
+      --prompt-template internlm-2-tool \
+      --ctx-size 32000 \
+      --model-name internlm2_5-20b-chat
+    ```
+
+- Run as LlamaEdge command app
+
+  ```bash
+  wasmedge --dir .:. \
+    --nn-preload default:GGML:AUTO:internlm2_5-20b-chat-Q5_K_M.gguf \
+    llama-chat.wasm \
+    --prompt-template chatml \
+    --ctx-size 32000
+  ```
+
+## Quantized GGUF Models
+
+| Name | Quant method | Bits | Size | Use case |
+| ---- | ---- | ---- | ---- | ----- |
+| [internlm2_5-20b-chat-Q2_K.gguf](https://huggingface.co/second-state/internlm2_5-20b-chat-GGUF/blob/main/internlm2_5-20b-chat-Q2_K.gguf)     | Q2_K   | 2 | 7.55 GB| smallest, significant quality loss - not recommended for most purposes |
+| [internlm2_5-20b-chat-Q3_K_L.gguf](https://huggingface.co/second-state/internlm2_5-20b-chat-GGUF/blob/main/internlm2_5-20b-chat-Q3_K_L.gguf) | Q3_K_L | 3 | 10.6 GB| small, substantial quality loss |
+| [internlm2_5-20b-chat-Q3_K_M.gguf](https://huggingface.co/second-state/internlm2_5-20b-chat-GGUF/blob/main/internlm2_5-20b-chat-Q3_K_M.gguf) | Q3_K_M | 3 | 9.72 GB| very small, high quality loss |
+| [internlm2_5-20b-chat-Q3_K_S.gguf](https://huggingface.co/second-state/internlm2_5-20b-chat-GGUF/blob/main/internlm2_5-20b-chat-Q3_K_S.gguf) | Q3_K_S | 3 | 8.76 GB| very small, high quality loss |
+| [internlm2_5-20b-chat-Q4_0.gguf](https://huggingface.co/second-state/internlm2_5-20b-chat-GGUF/blob/main/internlm2_5-20b-chat-Q4_0.gguf)     | Q4_0   | 4 | 11.3 GB| legacy; small, very high quality loss - prefer using Q3_K_M |
+| [internlm2_5-20b-chat-Q4_K_M.gguf](https://huggingface.co/second-state/internlm2_5-20b-chat-GGUF/blob/main/internlm2_5-20b-chat-Q4_K_M.gguf) | Q4_K_M | 4 | 12.0 GB| medium, balanced quality - recommended |
+| [internlm2_5-20b-chat-Q4_K_S.gguf](https://huggingface.co/second-state/internlm2_5-20b-chat-GGUF/blob/main/internlm2_5-20b-chat-Q4_K_S.gguf) | Q4_K_S | 4 | 11.4 GB| small, greater quality loss |
+| [internlm2_5-20b-chat-Q5_0.gguf](https://huggingface.co/second-state/internlm2_5-20b-chat-GGUF/blob/main/internlm2_5-20b-chat-Q5_0.gguf)     | Q5_0   | 5 | 13.7 GB| legacy; medium, balanced quality - prefer using Q4_K_M |
+| [internlm2_5-20b-chat-Q5_K_M.gguf](https://huggingface.co/second-state/internlm2_5-20b-chat-GGUF/blob/main/internlm2_5-20b-chat-Q5_K_M.gguf) | Q5_K_M | 5 | 14.1 GB| large, very low quality loss - recommended |
+| [internlm2_5-20b-chat-Q5_K_S.gguf](https://huggingface.co/second-state/internlm2_5-20b-chat-GGUF/blob/main/internlm2_5-20b-chat-Q5_K_S.gguf) | Q5_K_S | 5 | 13.7 GB| large, low quality loss - recommended |
+| [internlm2_5-20b-chat-Q6_K.gguf](https://huggingface.co/second-state/internlm2_5-20b-chat-GGUF/blob/main/internlm2_5-20b-chat-Q6_K.gguf)     | Q6_K   | 6 | 16.3 GB| very large, extremely low quality loss |
+| [internlm2_5-20b-chat-Q8_0.gguf](https://huggingface.co/second-state/internlm2_5-20b-chat-GGUF/blob/main/internlm2_5-20b-chat-Q8_0.gguf)     | Q8_0   | 8 | 21.1 GB| very large, extremely low quality loss - not recommended |
+| [internlm2_5-20b-chat-f16.gguf](https://huggingface.co/second-state/internlm2_5-20b-chat-GGUF/blob/main/internlm2_5-20b-chat-f16.gguf)       | f16    | 16 | 39.7 GB|  |
+
+*Quantized with llama.cpp b3499*

config.json

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+{
+  "architectures": [
+    "InternLM2ForCausalLM"
+  ],
+  "attn_implementation": "eager",
+  "auto_map": {
+    "AutoConfig": "configuration_internlm2.InternLM2Config",
+    "AutoModel": "modeling_internlm2.InternLM2ForCausalLM",
+    "AutoModelForCausalLM": "modeling_internlm2.InternLM2ForCausalLM",
+    "AutoModelForSequenceClassification": "modeling_internlm2.InternLM2ForSequenceClassification"
+  },
+  "bias": false,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 6144,
+  "initializer_range": 0.02,
+  "intermediate_size": 16384,
+  "max_position_embeddings": 32768,
+  "model_type": "internlm2",
+  "num_attention_heads": 48,
+  "num_hidden_layers": 48,
+  "num_key_value_heads": 8,
+  "pad_token_id": 2,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
+    "type": "dynamic",
+    "factor": 2.5
+  },
+  "rope_theta": 50000000,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.41.0",
+  "use_cache": true,
+  "vocab_size": 92544
+}

configuration.json

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+{"framework": "pytorch", "task": "text-generation", "allow_remote": true}

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