Text Generation
Transformers
Safetensors
kimi_k2
conversational
custom_code
Eval Results
compressed-tensors
Instructions to use moonshotai/Kimi-K2-Thinking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moonshotai/Kimi-K2-Thinking with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="moonshotai/Kimi-K2-Thinking", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("moonshotai/Kimi-K2-Thinking", trust_remote_code=True, dtype="auto") - Inference
- HuggingChat
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use moonshotai/Kimi-K2-Thinking with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "moonshotai/Kimi-K2-Thinking" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "moonshotai/Kimi-K2-Thinking", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/moonshotai/Kimi-K2-Thinking
- SGLang
How to use moonshotai/Kimi-K2-Thinking 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 "moonshotai/Kimi-K2-Thinking" \ --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": "moonshotai/Kimi-K2-Thinking", "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 "moonshotai/Kimi-K2-Thinking" \ --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": "moonshotai/Kimi-K2-Thinking", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use moonshotai/Kimi-K2-Thinking with Docker Model Runner:
docker model run hf.co/moonshotai/Kimi-K2-Thinking
| {%- macro render_content(msg) -%} | |
| {%- set c = msg.get('content') -%} | |
| {%- if c is string -%} | |
| {{ c }} | |
| {%- elif c is not none -%} | |
| {% for content in c -%} | |
| {% if content['type'] == 'image' or 'image' in content or 'image_url' in content -%} | |
| <|media_start|>image<|media_content|><|media_pad|><|media_end|> | |
| {% else -%} | |
| {{ content['text'] }} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {%- endif -%} | |
| {%- endmacro -%} | |
| {% macro set_roles(message) -%} | |
| {%- set role_name = message.get('name') or message['role'] -%} | |
| {%- if message['role'] == 'user' -%} | |
| <|im_user|>{{role_name}}<|im_middle|> | |
| {%- elif message['role'] == 'assistant' -%} | |
| <|im_assistant|>{{role_name}}<|im_middle|> | |
| {%- else -%} | |
| <|im_system|>{{role_name}}<|im_middle|> | |
| {%- endif -%} | |
| {%- endmacro -%} | |
| {%- macro render_toolcalls(message) -%} | |
| <|tool_calls_section_begin|> | |
| {%- for tool_call in message['tool_calls'] -%} | |
| {%- set formatted_id = tool_call['id'] -%} | |
| <|tool_call_begin|>{{ formatted_id }}<|tool_call_argument_begin|>{% if tool_call['function']['arguments'] is string %}{{ tool_call['function']['arguments'] }}{% else %}{{ tool_call['function']['arguments'] | tojson }}{% endif %}<|tool_call_end|> | |
| {%- endfor -%} | |
| <|tool_calls_section_end|> | |
| {%- endmacro -%} | |
| {# Find last non-tool-call assisitant message #} | |
| {%- set ns = namespace(last_non_tool_call_assistant_msg=-1) -%} | |
| {%- for idx in range(messages|length-1, -1, -1) -%} | |
| {%- if messages[idx]['role'] == 'assistant' and not messages[idx].get('tool_calls') -%} | |
| {%- set ns.last_non_tool_call_assistant_msg = idx -%} | |
| {%- break -%} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {# split all messages into history & suffix, reasoning_content in suffix should be reserved.#} | |
| {%- set hist_msgs = messages[:ns.last_non_tool_call_assistant_msg+1] -%} | |
| {%- set suffix_msgs = messages[ns.last_non_tool_call_assistant_msg+1:] -%} | |
| {%- if tools -%} | |
| <|im_system|>tool_declare<|im_middle|>{{ tools | tojson(separators=(',', ':')) }}<|im_end|> | |
| {%- endif -%} | |
| {%- if messages|length == 0 or messages[0]['role'] != 'system' -%} | |
| <|im_system|>system<|im_middle|>You are Kimi, an AI assistant created by Moonshot AI.<|im_end|> | |
| {%- endif -%} | |
| {%- for message in hist_msgs -%} | |
| {{set_roles(message)}} | |
| {%- if message['role'] == 'assistant' -%} | |
| <think></think>{{render_content(message)}} | |
| {%- if message.get('tool_calls') -%} | |
| {{render_toolcalls(message)}} | |
| {%- endif -%} | |
| {%- elif message['role'] == 'tool' -%} | |
| {%- set tool_call_id = message.tool_call_id -%} | |
| ## Return of {{ tool_call_id }} | |
| {{render_content(message)}} | |
| {%- elif message['content'] is not none -%} | |
| {{render_content(message)}} | |
| {%- endif -%} | |
| <|im_end|> | |
| {%- endfor -%} | |
| {%- for message in suffix_msgs -%} | |
| {{set_roles(message)}} | |
| {%- if message['role'] == 'assistant' -%} | |
| {%- set rc = message.get('reasoning_content', '') -%} | |
| <think>{{rc}}</think>{{render_content(message)}} | |
| {%- if message.get('tool_calls') -%} | |
| {{render_toolcalls(message)}} | |
| {%- endif -%} | |
| {%- elif message['role'] == 'tool' -%} | |
| {%- set tool_call_id = message.tool_call_id -%} | |
| ## Return of {{ tool_call_id }} | |
| {{render_content(message)}} | |
| {%- elif message['content'] is not none -%} | |
| {{render_content(message)}} | |
| {%- endif -%} | |
| <|im_end|> | |
| {%- endfor -%} | |
| {%- if add_generation_prompt -%} | |
| <|im_assistant|>assistant<|im_middle|> | |
| {%- endif -%} |