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# Nemotron / Minitron

[NVIDIA Nemotron](https://www.nvidia.com/en-us/ai-data-science/foundation-models/) and [Minitron](https://developer.nvidia.com/blog/how-to-prune-and-distill-llama-3-1-8b-to-an-nvidia-llama-3-1-minitron-4b-model/) are NVIDIA's family of language models. Minitron models are produced by pruning and distilling larger Llama/Nemotron models into compact, high-performance checkpoints.

|                  |                                         |
| ---------------- | --------------------------------------- |
| **Task**         | Text Generation                         |
| **Architecture** | `NemotronForCausalLM`                   |
| **Parameters**   | 8B                                      |
| **HF Org**       | [nvidia](https://huggingface.co/nvidia) |

## Available Models

* **Minitron-8B-Base**: pruned and distilled from Llama-3.1-8B

## Architecture

* `NemotronForCausalLM`

## Example HF Models

| Model            | HF ID                                                                       |
| ---------------- | --------------------------------------------------------------------------- |
| Minitron 8B Base | [`nvidia/Minitron-8B-Base`](https://huggingface.co/nvidia/Minitron-8B-Base) |

## Try with NeMo AutoModel

Install NeMo AutoModel and follow the fine-tuning guide to configure a recipe for this model.

**1. Install** ([full instructions](/get-started/installation)):

```bash
pip install nemo-automodel
```

**2. Clone the repo** to get example recipes you can adapt:

```bash
git clone https://github.com/NVIDIA-NeMo/Automodel.git
cd Automodel
```

**3. Fine-tune** by adapting a base LLM recipe — override the model ID on the CLI:

```bash
automodel --nproc-per-node=8 examples/llm_finetune/llama3_2/llama3_2_1b_squad.yaml \
  --model.pretrained_model_name_or_path <MODEL_HF_ID>
```

Replace `<MODEL_HF_ID>` with the model ID from **Example HF Models** above.

**1. Pull the container** and mount a checkpoint directory:

```bash
docker run --gpus all -it --rm \
  --shm-size=8g \
  -v $(pwd)/checkpoints:/opt/Automodel/checkpoints \
  nvcr.io/nvidia/nemo-automodel:26.04.00
```

**2.** The recipes are at `/opt/Automodel/examples/` — navigate there:

```bash
cd /opt/Automodel
```

**3. Fine-tune**:

```bash
automodel --nproc-per-node=8 examples/llm_finetune/llama3_2/llama3_2_1b_squad.yaml \
  --model.pretrained_model_name_or_path <MODEL_HF_ID>
```

See the [Installation Guide](/get-started/installation) and [LLM Fine-Tuning Guide](/recipes-e2e-examples/sft-peft).

## Fine-Tuning

See the [LLM Fine-Tuning Guide](/recipes-e2e-examples/sft-peft).

## Hugging Face Model Cards

* [nvidia/Minitron-8B-Base](https://huggingface.co/nvidia/Minitron-8B-Base)