> 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.

# NVIDIA-Nemotron-Parse-v1.1

> Use NVIDIA-Nemotron-Parse-v1.1 with NeMo AutoModel for vision-language fine-tuning, with documented checkpoints, runnable recipes, setup, and model reference details.

[Nemotron-Parse-v1.1](https://huggingface.co/nvidia/NVIDIA-Nemotron-Parse-v1.1) is NVIDIA's document parsing VLM, specializing in extracting structured information from complex documents including tables, forms, and mixed-content PDFs.

Set up NeMo AutoModel with the [latest container](https://catalog.ngc.nvidia.com/orgs/nvidia/containers/nemo-automodel) or follow the [installation instructions](/get-started/installation).

## Fine-Tune NVIDIA-Nemotron-Parse-v1.1

From the repository root, run:

```bash
uv run automodel --nproc-per-node=8 examples/vlm_finetune/nemotron/nemotron_parse_v1_1.yaml
```

## Choose a Workflow

| Goal                                                     | Start Here                                                                                                                                                                                                                                                                                                                                      |
| -------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Supervised fine-tuning (SFT) - Nemotron-Parse on CORD-v2 | Use [nemotron\_parse\_v1\_1.yaml](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/vlm_finetune/nemotron/nemotron_parse_v1_1.yaml). Dataset: cord-v2. [![Launch on Brev](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://brev.nvidia.com/launchable/deploy/now?launchableID=env-3C6LDKU2DfOvpVTFhjw3YQ4djPM) |

## Fine-Tuning Tutorial on Brev

Launch the end-to-end Nemotron Parse fine-tuning tutorial on Brev with a single click:

[![Launch on Brev](https://brev-assets.s3.us-west-1.amazonaws.com/nv-lb-dark.svg)](https://brev.nvidia.com/launchable/deploy/now?launchableID=env-3C6LDKU2DfOvpVTFhjw3YQ4djPM)

See also the [tutorial notebook](https://github.com/NVIDIA-NeMo/Automodel/blob/main/tutorials/nemotron-parse/finetune.ipynb) and the [VLM Fine-Tuning Guide](/recipes-e2e-examples/gemma-3-3n).

## Model Reference

### Model Architecture

| Property                  | Value                                   |
| ------------------------- | --------------------------------------- |
| Task                      | Document Parsing                        |
| Architecture              | `NemotronParseForConditionalGeneration` |
| Parameters                | \< 1B                                   |
| Hugging Face Organization | [nvidia](https://huggingface.co/nvidia) |

### Available Models

| Model               | HF ID                                                                                           |
| ------------------- | ----------------------------------------------------------------------------------------------- |
| Nemotron-Parse v1.1 | [`nvidia/NVIDIA-Nemotron-Parse-v1.1`](https://huggingface.co/nvidia/NVIDIA-Nemotron-Parse-v1.1) |

## Related Resources

* [VLM Fine-Tuning Guide](/recipes-e2e-examples/gemma-3-3n)