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> For a complete documentation index, see https://docs.nvidia.com/nemo/automodel/llms.txt.
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# GPT-J

[GPT-J](https://github.com/kingoflolz/mesh-transformer-jax) is a 6B parameter transformer language model trained by EleutherAI on the Pile dataset. It was one of the earliest large open-weight models.

|                  |                                                 |
| ---------------- | ----------------------------------------------- |
| **Task**         | Text Generation                                 |
| **Architecture** | `GPTJForCausalLM`                               |
| **Parameters**   | 6B                                              |
| **HF Org**       | [EleutherAI](https://huggingface.co/EleutherAI) |

## Available Models

* **gpt-j-6b**: 6B parameters
* **gpt4all-j**: GPT-J fine-tuned for instruction following (Nomic AI)

## Architecture

* `GPTJForCausalLM`

## Example HF Models

| Model     | HF ID                                                               |
| --------- | ------------------------------------------------------------------- |
| GPT-J 6B  | [`EleutherAI/gpt-j-6b`](https://huggingface.co/EleutherAI/gpt-j-6b) |
| GPT4All-J | [`nomic-ai/gpt4all-j`](https://huggingface.co/nomic-ai/gpt4all-j)   |

## 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:26.06.00
```

**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

* [EleutherAI/gpt-j-6b](https://huggingface.co/EleutherAI/gpt-j-6b)