> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/nemo/automodel/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo/automodel/_mcp/server.

# Granite

[IBM Granite](https://www.ibm.com/granite) is IBM's family of enterprise-focused language models. Granite 3.x models are trained on a mix of code and language data and are optimized for enterprise tasks including summarization, classification, and RAG. PowerLM (IBM Research) also uses this architecture.

|                  |                                                   |
| ---------------- | ------------------------------------------------- |
| **Task**         | Text Generation                                   |
| **Architecture** | `GraniteForCausalLM`                              |
| **Parameters**   | 2B – 8B                                           |
| **HF Org**       | [ibm-granite](https://huggingface.co/ibm-granite) |

## Available Models

* **Granite 3.3 2B Instruct**
* **Granite 3.1 8B Instruct**
* **Granite 3.0 2B Base**
* **PowerLM-3B** (IBM Research)

## Architecture

* `GraniteForCausalLM`

## Example HF Models

| Model                   | HF ID                                                                                               |
| ----------------------- | --------------------------------------------------------------------------------------------------- |
| Granite 3.0 2B Base     | [`ibm-granite/granite-3.0-2b-base`](https://huggingface.co/ibm-granite/granite-3.0-2b-base)         |
| Granite 3.1 8B Instruct | [`ibm-granite/granite-3.1-8b-instruct`](https://huggingface.co/ibm-granite/granite-3.1-8b-instruct) |
| PowerLM 3B              | [`ibm/PowerLM-3b`](https://huggingface.co/ibm/PowerLM-3b)                                           |

## Example Recipes

| Recipe                                                                                                                                                                    | Description                             |
| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------- |
| [granite\_3\_3\_2b\_instruct\_squad.yaml](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_finetune/granite/granite_3_3_2b_instruct_squad.yaml)            | SFT — Granite 3.3 2B Instruct on SQuAD  |
| [granite\_3\_3\_2b\_instruct\_squad\_peft.yaml](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_finetune/granite/granite_3_3_2b_instruct_squad_peft.yaml) | LoRA — Granite 3.3 2B Instruct on SQuAD |

## Try with NeMo AutoModel

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

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

**2. Clone the repo** to get the example recipes:

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

**3. Run the recipe** from inside the repo:

```bash
automodel --nproc-per-node=8 examples/llm_finetune/granite/granite_3_3_2b_instruct_squad.yaml
```

**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:26.06.00
```

**2.** Navigate to the AutoModel directory (where the recipes are):

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

**3. Run the recipe**:

```bash
automodel --nproc-per-node=8 examples/llm_finetune/granite/granite_3_3_2b_instruct_squad.yaml
```

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

* [ibm-granite/granite-3.0-2b-base](https://huggingface.co/ibm-granite/granite-3.0-2b-base)
* [ibm-granite/granite-3.1-8b-instruct](https://huggingface.co/ibm-granite/granite-3.1-8b-instruct)