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# MiniMax-M2 Model Repository
This is the official MiniMax-M2 model repository containing a 230B parameter MoE model with 10B active parameters, optimized for coding and agentic workflows.
## Model Information
- **Model Type**: Mixture of Experts (MoE)
- **Total Parameters**: 230B
- **Active Parameters**: 10B
- **Architecture**: Transformer-based MoE
- **License**: Modified MIT
- **Pipeline Tag**: text-generation
## Usage
This model can be used with various inference frameworks:
### Transformers
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("your-username/MiniMax-M2")
tokenizer = AutoTokenizer.from_pretrained("your-username/MiniMax-M2")
```
### vLLM
```python
from vllm import LLM, SamplingParams
llm = LLM(model="your-username/MiniMax-M2")
```
### SGLang
```python
from sglang import function, system, user, assistant, gen, select
@function
def multi_turn_question(s, question):
s += system("You are a helpful assistant.")
s += user(question)
s += assistant(gen("answer", max_tokens=256))
return s["answer"]
```
## Model Details
- **Context Length**: 128K tokens
- **Thinking Format**: Uses `<think>...</think>` tags for reasoning
- **Recommended Parameters**:
- Temperature: 1.0
- Top-p: 0.95
- Top-k: 40
## Deployment Guides
See the `docs/` directory for detailed deployment guides:
- [Transformers Guide](docs/transformers_deploy_guide.md)
- [vLLM Guide](docs/vllm_deploy_guide.md)
- [SGLang Guide](docs/sglang_deploy_guide.md)
- [MLX Guide](docs/mlx_deploy_guide.md)
## License
This model is released under the Modified MIT License. See the [license file](https://github.com/MiniMax-AI/MiniMax-M2/blob/main/LICENSE) for details. |