Visual Document Retrieval
Transformers
Safetensors
ColPali
multilingual
qwen3_vl_nemotron_embed
feature-extraction
text
image
vidore
multimodal-embedding
multilingual-embedding
Text-to-Visual Document (T→VD) retrieval
custom_code
Instructions to use nvidia/nemotron-colembed-vl-4b-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/nemotron-colembed-vl-4b-v2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nvidia/nemotron-colembed-vl-4b-v2", trust_remote_code=True, dtype="auto") - ColPali
How to use nvidia/nemotron-colembed-vl-4b-v2 with ColPali:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Ctrl+K