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copy-pr-bot bot commented Oct 31, 2025

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@github-actions github-actions bot added documentation Improvements or additions to documentation deploy TensorRT-LLM multimodal labels Oct 31, 2025

1. Follow the steps on the [Generate A NeMo 2.0 Checkpoint page](gen_nemo2_ckpt.md) to generate a NeMo 2.0 multimodal checkpoint.

2. In a terminal, go to the folder where the ``qwen2_vl_3b`` is located. Pull and run the Docker container image using the command shown below. Change the ``:vr`` tag to the version of the container you want to use:
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The model generated in gen_nemo2_ckpt.md and the one used here qwen2_vl_3b do not match. Could you please to use the one generated here?

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@oyilmaz-nvidia I've update the section in docs.

## Generate Qwen VL Checkpoint (for In-Framework Deployment)
This checkpoint is used for in-framework deployment examples.
3. Run the following Python code to generate the NeMo 2.0 checkpoint:
```python
from nemo.collections.llm import import_ckpt
from nemo.collections import vlm
from pathlib import Path
if __name__ == '__main__':
# Specify the Hugging Face model ID
hf_model_id = "Qwen/Qwen2.5-VL-3B-Instruct"
# Import the model and convert to NeMo 2.0 format
import_ckpt(
model=vlm.Qwen2VLModel(vlm.Qwen25VLConfig3B(), model_version='qwen25-vl')
source=f"hf://{hf_model_id}", # Hugging Face model source
output_path=Path('/opt/checkpoints/qwen25_vl_3b')
)
```

@github-actions github-actions bot added the export label Nov 4, 2025
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