diff --git a/xinference/model/llm/llm_family.json b/xinference/model/llm/llm_family.json
index 77dda1a84d..70b17daa61 100644
--- a/xinference/model/llm/llm_family.json
+++ b/xinference/model/llm/llm_family.json
@@ -7244,5 +7244,365 @@
         "model_revision": "00e59e64f47d3c78e4cfbdd345888479797e8109"
       }
     ]
+  },
+  {
+    "version": 1,
+    "context_length": 131072,
+    "model_name": "qwen2.5-instruct",
+    "model_lang": [
+      "en",
+      "zh"
+    ],
+    "model_ability": [
+      "chat",
+      "tools"
+    ],
+    "model_description": "Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters.",
+    "model_specs": [
+      {
+        "model_format": "pytorch",
+        "model_size_in_billions": "0_5",
+        "quantizations": [
+          "4-bit",
+          "8-bit",
+          "none"
+        ],
+        "model_id": "Qwen/Qwen2.5-0.5B-Instruct"
+      },
+      {
+        "model_format": "pytorch",
+        "model_size_in_billions": "1_5",
+        "quantizations": [
+          "4-bit",
+          "8-bit",
+          "none"
+        ],
+        "model_id": "Qwen/Qwen2.5-1.5B-Instruct"
+      },
+      {
+        "model_format": "pytorch",
+        "model_size_in_billions": 3,
+        "quantizations": [
+          "4-bit",
+          "8-bit",
+          "none"
+        ],
+        "model_id": "Qwen/Qwen2.5-3B-Instruct"
+      },
+      {
+        "model_format": "pytorch",
+        "model_size_in_billions": 7,
+        "quantizations": [
+          "4-bit",
+          "8-bit",
+          "none"
+        ],
+        "model_id": "Qwen/Qwen2.5-7B-Instruct"
+      },
+      {
+        "model_format": "pytorch",
+        "model_size_in_billions": 14,
+        "quantizations": [
+          "4-bit",
+          "8-bit",
+          "none"
+        ],
+        "model_id": "Qwen/Qwen2.5-14B-Instruct"
+      },
+      {
+        "model_format": "pytorch",
+        "model_size_in_billions": 32,
+        "quantizations": [
+          "4-bit",
+          "8-bit",
+          "none"
+        ],
+        "model_id": "Qwen/Qwen2.5-32B-Instruct"
+      },
+      {
+        "model_format": "pytorch",
+        "model_size_in_billions": 72,
+        "quantizations": [
+          "4-bit",
+          "8-bit",
+          "none"
+        ],
+        "model_id": "Qwen/Qwen2.5-72B-Instruct"
+      },
+      {
+        "model_format": "gptq",
+        "model_size_in_billions": "0_5",
+        "quantizations": [
+          "Int4",
+          "Int8"
+        ],
+        "model_id": "Qwen/Qwen2.5-0.5B-Instruct-GPTQ-{quantization}"
+      },
+      {
+        "model_format": "gptq",
+        "model_size_in_billions": "1_5",
+        "quantizations": [
+          "Int4",
+          "Int8"
+        ],
+        "model_id": "Qwen/Qwen2.5-1.5B-Instruct-GPTQ-{quantization}"
+      },
+      {
+        "model_format": "gptq",
+        "model_size_in_billions": 3,
+        "quantizations": [
+          "Int4",
+          "Int8"
+        ],
+        "model_id": "Qwen/Qwen2.5-3B-Instruct-GPTQ-{quantization}"
+      },
+      {
+        "model_format": "gptq",
+        "model_size_in_billions": 7,
+        "quantizations": [
+          "Int4",
+          "Int8"
+        ],
+        "model_id": "Qwen/Qwen2.5-7B-Instruct-GPTQ-{quantization}"
+      },
+      {
+        "model_format": "gptq",
+        "model_size_in_billions": 14,
+        "quantizations": [
+          "Int4",
+          "Int8"
+        ],
+        "model_id": "Qwen/Qwen2.5-14B-Instruct-GPTQ-{quantization}"
+      },
+      {
+        "model_format": "gptq",
+        "model_size_in_billions": 32,
+        "quantizations": [
+          "Int4",
+          "Int8"
+        ],
+        "model_id": "Qwen/Qwen2.5-32B-Instruct-GPTQ-{quantization}"
+      },
+      {
+        "model_format": "gptq",
+        "model_size_in_billions": 72,
+        "quantizations": [
+          "Int4",
+          "Int8"
+        ],
+        "model_id": "Qwen/Qwen2.5-72B-Instruct-GPTQ-{quantization}"
+      },
+      {
+        "model_format": "awq",
+        "model_size_in_billions": "0_5",
+        "quantizations": [
+          "Int4"
+        ],
+        "model_id": "Qwen/Qwen2.5-0.5B-Instruct-AWQ"
+      },
+      {
+        "model_format": "awq",
+        "model_size_in_billions": "1_5",
+        "quantizations": [
+          "Int4"
+        ],
+        "model_id": "Qwen/Qwen2.5-1.5B-Instruct-AWQ"
+      },
+      {
+        "model_format": "awq",
+        "model_size_in_billions": 3,
+        "quantizations": [
+          "Int4"
+        ],
+        "model_id": "Qwen/Qwen2.5-3B-Instruct-AWQ"
+      },
+      {
+        "model_format": "awq",
+        "model_size_in_billions": 7,
+        "quantizations": [
+          "Int4"
+        ],
+        "model_id": "Qwen/Qwen2.5-7B-Instruct-AWQ"
+      },
+      {
+        "model_format": "awq",
+        "model_size_in_billions": 14,
+        "quantizations": [
+          "Int4"
+        ],
+        "model_id": "Qwen/Qwen2.5-14B-Instruct-AWQ"
+      },
+      {
+        "model_format": "awq",
+        "model_size_in_billions": 32,
+        "quantizations": [
+          "Int4"
+        ],
+        "model_id": "Qwen/Qwen2.5-32B-Instruct-AWQ"
+      },
+      {
+        "model_format": "awq",
+        "model_size_in_billions": 72,
+        "quantizations": [
+          "Int4"
+        ],
+        "model_id": "Qwen/Qwen2.5-72B-Instruct-AWQ"
+      },
+      {
+        "model_format": "ggufv2",
+        "model_size_in_billions": "0_5",
+        "quantizations": [
+          "q2_k",
+          "q3_k_m",
+          "q4_0",
+          "q4_k_m",
+          "q5_0",
+          "q5_k_m",
+          "q6_k",
+          "q8_0",
+          "fp16"
+        ],
+        "model_id": "Qwen/Qwen2.5-0.5B-Instruct-GGUF",
+        "model_file_name_template": "qwen2_5-0_5b-instruct-{quantization}.gguf"
+      },
+      {
+        "model_format": "ggufv2",
+        "model_size_in_billions": "1_5",
+        "quantizations": [
+          "q2_k",
+          "q3_k_m",
+          "q4_0",
+          "q4_k_m",
+          "q5_0",
+          "q5_k_m",
+          "q6_k",
+          "q8_0",
+          "fp16"
+        ],
+        "model_id": "Qwen/Qwen2.5-1.5B-Instruct-GGUF",
+        "model_file_name_template": "qwen2_5-1_5b-instruct-{quantization}.gguf"
+      },
+      {
+        "model_format": "ggufv2",
+        "model_size_in_billions": 3,
+        "quantizations": [
+          "q2_k",
+          "q3_k_m",
+          "q4_0",
+          "q4_k_m",
+          "q5_0",
+          "q5_k_m",
+          "q6_k",
+          "q8_0",
+          "fp16"
+        ],
+        "model_id": "Qwen/Qwen2.5-3B-Instruct-GGUF",
+        "model_file_name_template": "qwen2_5-3b-instruct-{quantization}.gguf"
+      },
+      {
+        "model_format": "ggufv2",
+        "model_size_in_billions": 7,
+        "quantizations": [
+          "q2_k",
+          "q3_k_m",
+          "q4_0",
+          "q4_k_m",
+          "q5_0",
+          "q5_k_m",
+          "q6_k",
+          "q8_0",
+          "fp16"
+        ],
+        "model_id": "Qwen/Qwen2.5-7B-Instruct-GGUF",
+        "model_file_name_template": "qwen2_5-7b-instruct-{quantization}.gguf"
+      },
+      {
+        "model_format": "ggufv2",
+        "model_size_in_billions": 14,
+        "quantizations": [
+          "q2_k",
+          "q3_k_m",
+          "q4_0",
+          "q4_k_m",
+          "q5_0",
+          "q5_k_m",
+          "q6_k",
+          "q8_0",
+          "fp16"
+        ],
+        "model_id": "Qwen/Qwen2.5-14B-Instruct-GGUF",
+        "model_file_name_template": "qwen2_5-14b-instruct-{quantization}.gguf"
+      },
+      {
+        "model_format": "ggufv2",
+        "model_size_in_billions": 32,
+        "quantizations": [
+          "q2_k",
+          "q3_k_m",
+          "q4_0",
+          "q4_k_m",
+          "q5_0",
+          "q5_k_m",
+          "q6_k",
+          "q8_0",
+          "fp16"
+        ],
+        "model_id": "Qwen/Qwen2.5-32B-Instruct-GGUF",
+        "model_file_name_template": "qwen2_5-32b-instruct-{quantization}.gguf"
+      },
+      {
+        "model_format": "ggufv2",
+        "model_size_in_billions": 72,
+        "quantizations": [
+          "q2_k",
+          "q3_k_m",
+          "q4_0",
+          "q4_k_m",
+          "q5_0",
+          "q5_k_m",
+          "q6_k",
+          "q8_0",
+          "fp16"
+        ],
+        "model_id": "Qwen/Qwen2.5-72B-Instruct-GGUF",
+        "model_file_name_template": "qwen2_5-72b-instruct-{quantization}.gguf",
+        "model_file_name_split_template": "qwen2_5-72b-instruct-{quantization}-{part}.gguf",
+        "quantization_parts": {
+          "q5_0": [
+            "00001-of-00002",
+            "00002-of-00002"
+          ],
+          "q5_k_m": [
+            "00001-of-00002",
+            "00002-of-00002"
+          ],
+          "q6_k": [
+            "00001-of-00002",
+            "00002-of-00002"
+          ],
+          "q8_0": [
+            "00001-of-00002",
+            "00002-of-00002"
+          ],
+          "fp16": [
+            "00001-of-00004",
+            "00002-of-00004",
+            "00003-of-00004",
+            "00004-of-00004"
+          ]
+        }
+      }
+    ],
+    "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0]['role'] == 'system' %}\n        {{- messages[0]['content'] }}\n    {%- else %}\n        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n    {%- endif %}\n    {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0]['role'] == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n    {%- else %}\n        {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n        {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role }}\n        {%- if message.content %}\n            {{- '\\n' + message.content }}\n        {%- endif %}\n        {%- for tool_call in message.tool_calls %}\n            {%- if tool_call.function is defined %}\n                {%- set tool_call = tool_call.function %}\n            {%- endif %}\n            {{- '\\n<tool_call>\\n{\"name\": \"' }}\n            {{- tool_call.name }}\n            {{- '\", \"arguments\": ' }}\n            {{- tool_call.arguments | tojson }}\n            {{- '}\\n</tool_call>' }}\n        {%- endfor %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- message.content }}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
+    "stop_token_ids": [
+      151643,
+      151644,
+      151645
+    ],
+    "stop": [
+      "<|endoftext|>",
+      "<|im_start|>",
+      "<|im_end|>"
+    ]
   }
 ]
diff --git a/xinference/model/llm/llm_family_modelscope.json b/xinference/model/llm/llm_family_modelscope.json
index fdaab458aa..7309ee9651 100644
--- a/xinference/model/llm/llm_family_modelscope.json
+++ b/xinference/model/llm/llm_family_modelscope.json
@@ -4957,5 +4957,393 @@
         "model_revision": "master"
       }
     ]
+  },
+  {
+    "version": 1,
+    "context_length": 131072,
+    "model_name": "qwen2.5-instruct",
+    "model_lang": [
+      "en",
+      "zh"
+    ],
+    "model_ability": [
+      "chat",
+      "tools"
+    ],
+    "model_description": "Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters.",
+    "model_specs": [
+      {
+        "model_format": "pytorch",
+        "model_size_in_billions": "0_5",
+        "quantizations": [
+          "4-bit",
+          "8-bit",
+          "none"
+        ],
+        "model_id": "qwen/Qwen2.5-0.5B-Instruct",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "pytorch",
+        "model_size_in_billions": "1_5",
+        "quantizations": [
+          "4-bit",
+          "8-bit",
+          "none"
+        ],
+        "model_id": "qwen/Qwen2.5-1.5B-Instruct",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "pytorch",
+        "model_size_in_billions": 3,
+        "quantizations": [
+          "4-bit",
+          "8-bit",
+          "none"
+        ],
+        "model_id": "qwen/Qwen2.5-3B-Instruct",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "pytorch",
+        "model_size_in_billions": 7,
+        "quantizations": [
+          "4-bit",
+          "8-bit",
+          "none"
+        ],
+        "model_id": "qwen/Qwen2.5-7B-Instruct",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "pytorch",
+        "model_size_in_billions": 14,
+        "quantizations": [
+          "4-bit",
+          "8-bit",
+          "none"
+        ],
+        "model_id": "qwen/Qwen2.5-14B-Instruct",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "pytorch",
+        "model_size_in_billions": 32,
+        "quantizations": [
+          "4-bit",
+          "8-bit",
+          "none"
+        ],
+        "model_id": "qwen/Qwen2.5-32B-Instruct",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "pytorch",
+        "model_size_in_billions": 72,
+        "quantizations": [
+          "4-bit",
+          "8-bit",
+          "none"
+        ],
+        "model_id": "qwen/Qwen2.5-72B-Instruct",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "gptq",
+        "model_size_in_billions": "0_5",
+        "quantizations": [
+          "Int4",
+          "Int8"
+        ],
+        "model_id": "qwen/Qwen2.5-0.5B-Instruct-GPTQ-{quantization}",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "gptq",
+        "model_size_in_billions": "1_5",
+        "quantizations": [
+          "Int4",
+          "Int8"
+        ],
+        "model_id": "qwen/Qwen2.5-1.5B-Instruct-GPTQ-{quantization}",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "gptq",
+        "model_size_in_billions": 3,
+        "quantizations": [
+          "Int4",
+          "Int8"
+        ],
+        "model_id": "qwen/Qwen2.5-3B-Instruct-GPTQ-{quantization}",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "gptq",
+        "model_size_in_billions": 7,
+        "quantizations": [
+          "Int4",
+          "Int8"
+        ],
+        "model_id": "qwen/Qwen2.5-7B-Instruct-GPTQ-{quantization}",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "gptq",
+        "model_size_in_billions": 14,
+        "quantizations": [
+          "Int4",
+          "Int8"
+        ],
+        "model_id": "qwen/Qwen2.5-14B-Instruct-GPTQ-{quantization}",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "gptq",
+        "model_size_in_billions": 32,
+        "quantizations": [
+          "Int4",
+          "Int8"
+        ],
+        "model_id": "qwen/Qwen2.5-32B-Instruct-GPTQ-{quantization}",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "gptq",
+        "model_size_in_billions": 72,
+        "quantizations": [
+          "Int4",
+          "Int8"
+        ],
+        "model_id": "qwen/Qwen2.5-72B-Instruct-GPTQ-{quantization}",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "awq",
+        "model_size_in_billions": "0_5",
+        "quantizations": [
+          "Int4"
+        ],
+        "model_id": "qwen/Qwen2-0.5B-Instruct-AWQ",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "awq",
+        "model_size_in_billions": "1_5",
+        "quantizations": [
+          "Int4"
+        ],
+        "model_id": "qwen/Qwen2-1.5B-Instruct-AWQ",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "awq",
+        "model_size_in_billions": 3,
+        "quantizations": [
+          "Int4"
+        ],
+        "model_id": "qwen/Qwen2.5-3B-Instruct-AWQ",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "awq",
+        "model_size_in_billions": 7,
+        "quantizations": [
+          "Int4"
+        ],
+        "model_id": "qwen/Qwen2.5-7B-Instruct-AWQ",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "awq",
+        "model_size_in_billions":14,
+        "quantizations": [
+          "Int4"
+        ],
+        "model_id": "qwen/Qwen2.5-14B-Instruct-AWQ",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "awq",
+        "model_size_in_billions": 32,
+        "quantizations": [
+          "Int4"
+        ],
+        "model_id": "qwen/Qwen2.5-32B-Instruct-AWQ",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "awq",
+        "model_size_in_billions": 72,
+        "quantizations": [
+          "Int4"
+        ],
+        "model_id": "qwen/Qwen2.5-72B-Instruct-AWQ",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "ggufv2",
+        "model_size_in_billions": "0_5",
+        "quantizations": [
+          "q2_k",
+          "q3_k_m",
+          "q4_0",
+          "q4_k_m",
+          "q5_0",
+          "q5_k_m",
+          "q6_k",
+          "q8_0",
+          "fp16"
+        ],
+        "model_id": "qwen/Qwen2.5-0.5B-Instruct-GGUF",
+        "model_file_name_template": "qwen2_5-0_5b-instruct-{quantization}.gguf",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "ggufv2",
+        "model_size_in_billions": "1_5",
+        "quantizations": [
+          "q2_k",
+          "q3_k_m",
+          "q4_0",
+          "q4_k_m",
+          "q5_0",
+          "q5_k_m",
+          "q6_k",
+          "q8_0",
+          "fp16"
+        ],
+        "model_id": "qwen/Qwen2.5-1.5B-Instruct-GGUF",
+        "model_file_name_template": "qwen2_5-1_5b-instruct-{quantization}.gguf",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "ggufv2",
+        "model_size_in_billions": 3,
+        "quantizations": [
+          "q2_k",
+          "q3_k_m",
+          "q4_0",
+          "q4_k_m",
+          "q5_0",
+          "q5_k_m",
+          "q6_k",
+          "q8_0",
+          "fp16"
+        ],
+        "model_id": "qwen/Qwen2.5-3B-Instruct-GGUF",
+        "model_file_name_template": "qwen2_5-3b-instruct-{quantization}.gguf",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "ggufv2",
+        "model_size_in_billions": 7,
+        "quantizations": [
+          "q2_k",
+          "q3_k_m",
+          "q4_0",
+          "q4_k_m",
+          "q5_0",
+          "q5_k_m",
+          "q6_k",
+          "q8_0",
+          "fp16"
+        ],
+        "model_id": "qwen/Qwen2.5-7B-Instruct-GGUF",
+        "model_file_name_template": "qwen2_5-7b-instruct-{quantization}.gguf",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "ggufv2",
+        "model_size_in_billions": 14,
+        "quantizations": [
+          "q2_k",
+          "q3_k_m",
+          "q4_0",
+          "q4_k_m",
+          "q5_0",
+          "q5_k_m",
+          "q6_k",
+          "q8_0",
+          "fp16"
+        ],
+        "model_id": "qwen/Qwen2.5-14B-Instruct-GGUF",
+        "model_file_name_template": "qwen2_5-14b-instruct-{quantization}.gguf",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "ggufv2",
+        "model_size_in_billions": 32,
+        "quantizations": [
+          "q2_k",
+          "q3_k_m",
+          "q4_0",
+          "q4_k_m",
+          "q5_0",
+          "q5_k_m",
+          "q6_k",
+          "q8_0",
+          "fp16"
+        ],
+        "model_id": "qwen/Qwen2.5-32B-Instruct-GGUF",
+        "model_file_name_template": "qwen2_5-32b-instruct-{quantization}.gguf",
+        "model_hub": "modelscope"
+      },
+      {
+        "model_format": "ggufv2",
+        "model_size_in_billions": 72,
+        "quantizations": [
+          "q2_k",
+          "q3_k_m",
+          "q4_0",
+          "q4_k_m",
+          "q5_0",
+          "q5_k_m",
+          "q6_k",
+          "q8_0",
+          "fp16"
+        ],
+        "model_id": "qwen/Qwen2.5-72B-Instruct-GGUF",
+        "model_hub": "modelscope",
+        "model_file_name_template": "qwen2_5-72b-instruct-{quantization}.gguf",
+        "model_file_name_split_template": "qwen2_5-72b-instruct-{quantization}-{part}.gguf",
+        "quantization_parts": {
+          "q5_0": [
+            "00001-of-00002",
+            "00002-of-00002"
+          ],
+          "q5_k_m": [
+            "00001-of-00002",
+            "00002-of-00002"
+          ],
+          "q6_k": [
+            "00001-of-00002",
+            "00002-of-00002"
+          ],
+          "q8_0": [
+            "00001-of-00002",
+            "00002-of-00002"
+          ],
+          "fp16": [
+            "00001-of-00004",
+            "00002-of-00004",
+            "00003-of-00004",
+            "00004-of-00004"
+          ]
+        }
+      }
+    ],
+    "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0]['role'] == 'system' %}\n        {{- messages[0]['content'] }}\n    {%- else %}\n        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n    {%- endif %}\n    {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0]['role'] == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n    {%- else %}\n        {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n        {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role }}\n        {%- if message.content %}\n            {{- '\\n' + message.content }}\n        {%- endif %}\n        {%- for tool_call in message.tool_calls %}\n            {%- if tool_call.function is defined %}\n                {%- set tool_call = tool_call.function %}\n            {%- endif %}\n            {{- '\\n<tool_call>\\n{\"name\": \"' }}\n            {{- tool_call.name }}\n            {{- '\", \"arguments\": ' }}\n            {{- tool_call.arguments | tojson }}\n            {{- '}\\n</tool_call>' }}\n        {%- endfor %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- message.content }}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
+    "stop_token_ids": [
+      151643,
+      151644,
+      151645
+    ],
+    "stop": [
+      "<|endoftext|>",
+      "<|im_start|>",
+      "<|im_end|>"
+    ]
   }
 ]
diff --git a/xinference/model/llm/vllm/core.py b/xinference/model/llm/vllm/core.py
index 811fd5d342..3aaee0738f 100644
--- a/xinference/model/llm/vllm/core.py
+++ b/xinference/model/llm/vllm/core.py
@@ -138,6 +138,7 @@ class VLLMGenerateConfig(TypedDict, total=False):
     VLLM_SUPPORTED_MODELS.append("codeqwen1.5")
     VLLM_SUPPORTED_CHAT_MODELS.append("codeqwen1.5-chat")
     VLLM_SUPPORTED_CHAT_MODELS.append("qwen2-instruct")
+    VLLM_SUPPORTED_CHAT_MODELS.append("qwen2.5-instruct")
 
 if VLLM_INSTALLED and vllm.__version__ >= "0.3.2":
     VLLM_SUPPORTED_CHAT_MODELS.append("gemma-it")