Instructions to use unsloth/MiniMax-M2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use unsloth/MiniMax-M2 with Transformers:

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

pipe = pipeline("text-generation", model="unsloth/MiniMax-M2")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("unsloth/MiniMax-M2")
model = AutoModelForCausalLM.from_pretrained("unsloth/MiniMax-M2")
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 unsloth/MiniMax-M2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "unsloth/MiniMax-M2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "unsloth/MiniMax-M2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/unsloth/MiniMax-M2

SGLang

How to use unsloth/MiniMax-M2 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 "unsloth/MiniMax-M2" \
    --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": "unsloth/MiniMax-M2",
		"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 "unsloth/MiniMax-M2" \
        --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": "unsloth/MiniMax-M2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use unsloth/MiniMax-M2 with Docker Model Runner:
```
docker model run hf.co/unsloth/MiniMax-M2
```

danielhanchen commited on Nov 1, 2025

Commit

37316f3

verified ·

1 Parent(s): fe33316

Update chat_template.jinja

Browse files

Files changed (1) hide show

chat_template.jinja +2 -2

chat_template.jinja CHANGED Viewed

@@ -5,7 +5,7 @@
 {#- Tool Rendering Functions ============================================== -#}
 {%- macro render_tool_namespace(namespace_name, tool_list) -%}
 {%- for tool in tool_list -%}
-<tool>{{ tool.function | tojson(ensure_ascii=False) }}</tool>
 {% endfor -%}
 {%- endmacro -%}
 {%- macro visible_text(content) -%}
@@ -121,7 +121,7 @@
                 {% set _args = tool_call.arguments %}
                 {%- for k, v in _args.items() %}
                 {{- '<parameter name="' + k + '">' }}
-                {{- v | tojson(ensure_ascii=False) if v is not string else v }}
                 {{- '</parameter>' }}
                 {% endfor %}
                 {{- '</invoke>' ~ '\n' }}

 {#- Tool Rendering Functions ============================================== -#}
 {%- macro render_tool_namespace(namespace_name, tool_list) -%}
 {%- for tool in tool_list -%}
+<tool>{{ tool.function | tojson | string }}</tool>
 {% endfor -%}
 {%- endmacro -%}
 {%- macro visible_text(content) -%}
                 {% set _args = tool_call.arguments %}
                 {%- for k, v in _args.items() %}
                 {{- '<parameter name="' + k + '">' }}
+                {{- v | tojson | string if v is not string else v }}
                 {{- '</parameter>' }}
                 {% endfor %}
                 {{- '</invoke>' ~ '\n' }}