Instructions to use pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct")
model = AutoModelForCausalLM.from_pretrained("pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct

SGLang

How to use pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Studio

How to use pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct",
    max_seq_length=2048,
)

Docker Model Runner
How to use pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct with Docker Model Runner:
```
docker model run hf.co/pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct
```

MiniCPM5-1B-Hindi-Instruct / tokenizer_config.json

pankajpandey-dev

Upload MiniCPM5-1B Hindi Instruct (merged 16-bit)

ec6a1de verified 7 days ago

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	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130488": {
	"content": "<unused_token_406>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130489": {
	"content": "<unused_token_407>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130490": {
	"content": "<unused_token_408>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130491": {
	"content": "<unused_token_409>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130492": {
	"content": "<unused_token_410>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130493": {
	"content": "<unused_token_411>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130494": {
	"content": "<unused_token_412>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130495": {
	"content": "<unused_token_413>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130496": {
	"content": "<unused_token_414>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130497": {
	"content": "<unused_token_415>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130498": {
	"content": "<unused_token_416>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130499": {
	"content": "<unused_token_417>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130500": {
	"content": "<unused_token_418>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130501": {
	"content": "<unused_token_419>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130502": {
	"content": "<unused_token_420>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130503": {
	"content": "<unused_token_421>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130504": {
	"content": "<unused_token_422>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130505": {
	"content": "<unused_token_423>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130506": {
	"content": "<unused_token_424>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130507": {
	"content": "<unused_token_425>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130508": {
	"content": "<unused_token_426>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130509": {
	"content": "<unused_token_427>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130510": {
	"content": "<unused_token_428>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130511": {
	"content": "<unused_token_429>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130512": {
	"content": "<unused_token_430>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130513": {
	"content": "<unused_token_431>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130514": {
	"content": "<unused_token_432>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130515": {
	"content": "<unused_token_433>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130516": {
	"content": "<unused_token_434>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130517": {
	"content": "<unused_token_435>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130518": {
	"content": "<unused_token_436>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130519": {
	"content": "<unused_token_437>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130520": {
	"content": "<unused_token_438>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130521": {
	"content": "<unused_token_439>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130522": {
	"content": "<unused_token_440>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130523": {
	"content": "<unused_token_441>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130524": {
	"content": "<unused_token_442>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130525": {
	"content": "<unused_token_443>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130526": {
	"content": "<unused_token_444>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130527": {
	"content": "<unused_token_445>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130528": {
	"content": "<unused_token_446>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130529": {
	"content": "<unused_token_447>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130530": {
	"content": "<unused_token_448>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130531": {
	"content": "<unused_token_449>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130532": {
	"content": "<unused_token_450>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130533": {
	"content": "<unused_token_451>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130534": {
	"content": "<unused_token_452>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130535": {
	"content": "<unused_token_453>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130536": {
	"content": "<unused_token_454>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130537": {
	"content": "<unused_token_455>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130538": {
	"content": "<unused_token_456>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130539": {
	"content": "<unused_token_457>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130540": {
	"content": "<unused_token_458>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130541": {
	"content": "<unused_token_459>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130542": {
	"content": "<unused_token_460>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130543": {
	"content": "<unused_token_461>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130544": {
	"content": "<unused_token_462>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130545": {
	"content": "<unused_token_463>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130546": {
	"content": "<unused_token_464>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130547": {
	"content": "<unused_token_465>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130548": {
	"content": "<unused_token_466>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130549": {
	"content": "<unused_token_467>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130550": {
	"content": "<unused_token_468>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130551": {
	"content": "<unused_token_469>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130552": {
	"content": "<unused_token_470>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130553": {
	"content": "<unused_token_471>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130554": {
	"content": "<unused_token_472>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130555": {
	"content": "<unused_token_473>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130556": {
	"content": "<unused_token_474>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130557": {
	"content": "<unused_token_475>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130558": {
	"content": "<unused_token_476>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": true,
	"special": false
	},
	"130559": {
	"content": "<unused_token_477>",
	"single_word": false,
	"lstrip": false,
	"rstrip": false,
	"normalized": false,
	"special": true
	}
	},
	"chat_template": "{{- bos_token }}{%- if tools %}\n {%- set tool_definitions %}\n {{- \"# Tools\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool \| tojson(ensure_ascii=False) }}\n {%- endfor %}\n {{- '\\n</tools>\\n\\nTool usage guidelines:\\n- You may call zero or more functions. If no function calls are needed, just answer normally and do not include any <function ... </function>.\\n- When calling a function, return an XML object within <function ... </function> using:\\n<function name=\"function-name\"><param name=\"param-name\">param-value</param></function>\\n- param-value may be multi-line. If it contains <, & or newline characters, wrap it in a CDATA block: <param name=\"param-name\"><![CDATA[...multi-line value...]]></param>' }}\n {%- endset %}\n \n {{- '<\|im_start\|>system\\n' }}\n {%- if messages[0].role == 'system' %}\n {%- if '<tool_def_sep>' in messages[0].content %}\n {{- messages[0].content.replace('<tool_def_sep>', tool_definitions) }}\n {%- else %}\n {{- messages[0].content + '\\n\\n' + tool_definitions }}\n {%- endif %}\n {%- else %}\n {{- tool_definitions.lstrip() }}\n {%- endif %}\n {{- '<\|im_end\|>\\n' }}\n{%- else %}\n {%- if messages[0].role == 'system' %}\n {{- '<\|im_start\|>system\\n' + messages[0].content + '<\|im_end\|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages\|length - 1) %}\n{%- for message in messages[::-1] %}\n {%- set index = (messages\|length - 1) - loop.index0 %}\n {%- if ns.multi_step_tool and message.role == \"user\" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}\n {%- set ns.multi_step_tool = false %}\n {%- set ns.last_query_index = index %}\n {%- endif %}\n{%- endfor %}\n{%- for message in messages %}\n {%- if message.content is string %}\n {%- set content = message.content %}\n {%- else %}\n {%- set content = '' %}\n {%- endif %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n {{- '<\|im_start\|>' + message.role + '\\n' + content + '<\|im_end\|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {%- set reasoning_content = '' %}\n {%- if message.reasoning_content is string %}\n {%- set reasoning_content = message.reasoning_content %}\n {%- else %}\n {%- if '</think>' in content %}\n {%- set reasoning_content = content.split('</think>')[0].rstrip('\\n').split('<think>')[-1].lstrip('\\n') %}\n {%- set content = content.split('</think>')[-1].lstrip('\\n') %}\n {%- endif %}\n {%- endif %}\n \n {%- if message.tool_calls %}\n {%- set content_parts = content.split('<tool_sep>') %}\n {%- set processed_content = content_parts[0] %}\n {%- set tool_calls_count = message.tool_calls\|length %}\n {%- set tool_sep_count = content_parts\|length - 1 %}\n {%- set min_count = [tool_calls_count, tool_sep_count]\|min %}\n \n {%- for i in range(1, content_parts\|length) %}\n {%- set tool_index = i - 1 %}\n {%- if tool_index < tool_calls_count %}\n {%- set tool_call = message.tool_calls[tool_index] %}\n {%- if tool_call.function %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {%- set single_tool_xml %}\n {{- '<function name=\"' ~ tool_call.name ~ '\">' }}\n {%- if tool_call.arguments %}\n {%- set args_dict = tool_call.arguments %}\n {%- for param_name, param_value in args_dict.items() %}\n {{- '<param name=\"' ~ param_name ~ '\">' }}\n {%- if param_value is string and ('<' in param_value or '&' in param_value or '\\n' in param_value) %}\n {{- '<![CDATA[' + param_value + ']]>' }}\n {%- else %}\n {{- param_value }}\n {%- endif %}\n {{- '</param>' }}\n {%- endfor %}\n {%- endif %}\n {{- '</function>' }}\n {%- endset %}\n {%- set processed_content = processed_content + single_tool_xml + content_parts[i] %}\n {%- else %}\n {%- set processed_content = processed_content + content_parts[i] %}\n {%- endif %}\n {%- endfor %}\n \n {%- if tool_calls_count > tool_sep_count %}\n {%- for remaining_index in range(tool_sep_count, tool_calls_count) %}\n {%- set tool_call = message.tool_calls[remaining_index] %}\n {%- if tool_call.function %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {%- set remaining_tool_xml %}\n {{- '<function name=\"' ~ tool_call.name ~ '\">' }}\n {%- if tool_call.arguments %}\n {%- set args_dict = tool_call.arguments %}\n {%- for param_name, param_value in args_dict.items() %}\n {{- '<param name=\"' ~ param_name ~ '\">' }}\n {%- if param_value is string and ('<' in param_value or '&' in param_value or '\\n' in param_value) %}\n {{- '<![CDATA[' + param_value + ']]>' }}\n {%- else %}\n {{- param_value }}\n {%- endif %}\n {{- '</param>' }}\n {%- endfor %}\n {%- endif %}\n {{- '</function>' }}\n {%- endset %}\n {%- set processed_content = processed_content + remaining_tool_xml %}\n {%- endfor %}\n {%- endif %}\n \n {%- set content = processed_content %}\n {%- endif %}\n \n {%- if loop.index0 > ns.last_query_index %}\n {%- if reasoning_content %}\n {{- '<\|im_start\|>' + message.role + '\\n<think>\\n' + reasoning_content.strip('\\n') + '\\n</think>\\n\\n' + content.lstrip('\\n') }}\n {%- else %}\n {{- '<\|im_start\|>' + message.role + '\\n' + content }}\n {%- endif %}\n {%- else %}\n {{- '<\|im_start\|>' + message.role + '\\n' + content }}\n {%- endif %}\n \n {%- if message.tool_calls and not has_tool_sep %}\n {%- for tool_call in message.tool_calls %}\n {%- if (loop.first and content) or (not loop.first) %}\n {{- '\\n' }}\n {%- endif %}\n {%- if tool_call.function %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '<function name=\"' ~ tool_call.name ~ '\">' }}\n {%- if tool_call.arguments %}\n {%- set args_dict = tool_call.arguments %}\n {%- for param_name, param_value in args_dict.items() %}\n {{- '<param name=\"' ~ param_name ~ '\">' }}\n {%- if param_value is string and ('<' in param_value or '&' in param_value or '\\n' in param_value) %}\n {{- '<![CDATA[' + param_value + ']]>' }}\n {%- else %}\n {{- param_value }}\n {%- endif %}\n {{- '</param>' }}\n {%- endfor %}\n {%- endif %}\n {{- '</function>' }}\n {%- endfor %}\n {%- endif %}\n {{- '<\|im_end\|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<\|im_start\|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {%- if message.content is string %}\n {{- content }}\n {%- else %}\n {{- message.content \| tojson(ensure_ascii=False) }}\n {%- endif %}\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 {%- if enable_thinking is defined %}\n {%- if enable_thinking is false %}\n {{- '<think>\\n\\n</think>\\n\\n' }}\n {%- elif enable_thinking is true %}\n {{- '<think>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endif %}\n"
	}