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# MiniMax-M2.5

> Use NeMo AutoModel to fine-tune MiniMax-M2.5 for LLM workflows with checked-in text generation recipes and documented distributed settings.

[MiniMax-M2.5](https://huggingface.co/MiniMaxAI/MiniMax-M2.5) has a checked-in NeMo AutoModel recipe for text generation.
The Hugging Face configuration declares the `MiniMaxM2ForCausalLM` architecture.

## Fine-Tune MiniMax-M2.5

Follow the [installation instructions](/get-started/installation), then run the recipe from the repository root:

```bash
automodel examples/llm_finetune/minimax_m2/minimax_m2.5_hellaswag_pp.yaml --nproc-per-node 8
```

Use the [Slurm launcher guide](/job-launchers/slurm-cluster) for the multi-node run.

## Choose a Workflow

| Goal                                         | Start Here                                                                                                                                          |
| -------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------- |
| Run the primary recipe for this model        | Use the [recipe configuration](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_finetune/minimax_m2/minimax_m2.5_hellaswag_pp.yaml). |
| Try another checked-in recipe for this model | Use the [alternate recipe](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_benchmark/minimax/minimax_m2.5_te_deepep.yaml).          |

### Configuration

| Setting  | Configuration                                                   |
| -------- | --------------------------------------------------------------- |
| Hardware | -                                                               |
| Strategy | FSDP2; tp\_size=1, pp\_size=2, cp\_size=1, ep\_size=32          |
| Nodes    | 8                                                               |
| Features | Transformer Engine, HybridEP (dispatcher=hybridep)              |
| Advanced | attention=te, linear=te, experts=torch\_mm, dispatcher=hybridep |

### More Recipes for This Model

* [`minimax_m2.5_te_deepep.yaml`](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_benchmark/minimax/minimax_m2.5_te_deepep.yaml)
* [`minimax_m25_lora.yaml`](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_benchmark/minimax/minimax_m25_lora.yaml)

## Model Reference

### Model Architecture

| Property     | Value                  |
| ------------ | ---------------------- |
| Task         | Text generation        |
| Architecture | `MiniMaxM2ForCausalLM` |

### Available Models

* [`MiniMaxAI/MiniMax-M2.5`](https://huggingface.co/MiniMaxAI/MiniMax-M2.5)

## Related Resources

* [LLM fine-tuning guide](/recipes-e2e-examples/sft-peft)