InternVL#

InternVL is a vision language model from Shanghai AI Laboratory (OpenGVLab), combining a large vision encoder with an InternLM language backbone for strong multimodal performance.

Task

Image-Text-to-Text

Architecture

InternVLForConditionalGeneration

Parameters

4B – 8B

HF Org

OpenGVLab

Available Models#

  • InternVL3.5-4B

  • InternVL3.5-8B

Architecture#

  • InternVLForConditionalGeneration

Example HF Models#

Model

HF ID

InternVL3.5 4B

OpenGVLab/InternVL3-5-4B

Example Recipes#

Recipe

Dataset

Description

internvl_3_5_4b.yaml

MedPix-VQA

SFT — InternVL3.5 4B on MedPix

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/internvl/internvl_3_5_4b.yaml
Run with Docker

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:26.02.00

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/internvl/internvl_3_5_4b.yaml

See the Installation Guide and VLM Fine-Tuning Guide.

Fine-Tuning#

See the VLM Fine-Tuning Guide.

Hugging Face Model Cards#