Model CoverageVision Language Models (VLMs)

Nemotron-Parse

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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.

TaskDocument Parsing
ArchitectureNemotronParseForConditionalGeneration
Parametersvaries
HF Orgnvidia

Available Models

  • Nemotron-Parse-v1.1

Architecture

  • NemotronParseForConditionalGeneration

Example HF Models

ModelHF ID
Nemotron-Parse v1.1nvidia/Nemotron-Parse-v1.1

Example Recipes

RecipeDatasetDescriptionTry on Brev
nemotron_parse_v1_1.yamlcord-v2SFT — Nemotron-Parse on CORD-v2Launch on Brev

Try with NeMo AutoModel

1. Install (full instructions):

$pip install nemo-automodel

2. Clone the repo to get the example recipes:

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

3. Run the recipe from inside the repo:

$automodel --nproc-per-node=8 examples/vlm_finetune/nemotron/nemotron_parse_v1_1.yaml

1. Pull the container and mount a checkpoint directory:

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

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

$cd /opt/Automodel

3. Run the recipe:

$automodel --nproc-per-node=8 examples/vlm_finetune/nemotron/nemotron_parse_v1_1.yaml

See the Installation Guide and VLM Fine-Tuning Guide.

Fine-Tuning Tutorial on Brev

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

Launch on Brev

See also the tutorial notebook and the VLM Fine-Tuning Guide.

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