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# NVIDIA-Nemotron-3-Nano-30B-A3B-BF16

> Use NeMo AutoModel to fine-tune NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 for LLM workflows with checked-in text generation recipes and documented distributed settings.

[NVIDIA-Nemotron-3-Nano-30B-A3B-BF16](https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16) has a checked-in NeMo AutoModel recipe for text generation.
The Hugging Face configuration declares the `NemotronHForCausalLM` architecture.

## Fine-Tune NVIDIA-Nemotron-3-Nano-30B-A3B-BF16

Follow the [installation instructions](/get-started/installation), then review the checked-in recipe and
its declared topology below before choosing a local or cluster launcher.

```bash
uv run automodel examples/llm_finetune/nemotron/nemotron_nano_v3_cp_test.yaml \
  --nproc-per-node 8
```

## 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/nemotron/nemotron_nano_v3_cp_test.yaml). |
| Try another checked-in recipe for this model | Use the [alternate recipe](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_benchmark/nemotron/nemotron_nano_v3_te_deepep.yaml).  |

### Configuration

| Setting  | Configuration                                         |
| -------- | ----------------------------------------------------- |
| Hardware | -                                                     |
| Strategy | FSDP2; tp\_size=1, pp\_size=1, cp\_size=2, ep\_size=4 |
| Nodes    | -                                                     |
| Features | Transformer Engine                                    |
| Advanced | attention=te                                          |

### More Recipes for This Model

* [`nemotron_nano_v3_te_deepep.yaml`](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_benchmark/nemotron/nemotron_nano_v3_te_deepep.yaml)
* [`customizer_nemotron_nano_full_sft.yaml`](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_finetune/nemotron/customizer_nemotron_nano_full_sft.yaml)
* [`customizer_nemotron_nano_full_sft_chat.yaml`](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_finetune/nemotron/customizer_nemotron_nano_full_sft_chat.yaml)
* [`customizer_nemotron_nano_peft.yaml`](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_finetune/nemotron/customizer_nemotron_nano_peft.yaml)
* [`customizer_nemotron_nano_peft_packing.yaml`](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_finetune/nemotron/customizer_nemotron_nano_peft_packing.yaml)
* [`nemotron_nano_v3_hellaswag.yaml`](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_finetune/nemotron/nemotron_nano_v3_hellaswag.yaml)
* [`nemotron_nano_v3_hellaswag_peft.yaml`](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_finetune/nemotron/nemotron_nano_v3_hellaswag_peft.yaml)
* [`nemotron_nano_v3_hellaswag_peft_te.yaml`](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_finetune/nemotron/nemotron_nano_v3_hellaswag_peft_te.yaml)
* [`nemotron_nano_v3_singlegpu_lora.yaml`](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_finetune/nemotron/nemotron_nano_v3_singlegpu_lora.yaml)

## Model Reference

### Model Architecture

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

### Available Models

* [`nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16`](https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16)

## Related Resources

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