Visual Document Retrieval
Transformers
Safetensors
gemma3
image-text-to-text
vision-language
retrieval
colbert
late-interaction
multimodal
multilingual
document-retrieval
22-languages
Eval Results (legacy)
text-generation-inference
Instructions to use Cognitive-Lab/ColNetraEmbed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cognitive-Lab/ColNetraEmbed with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Cognitive-Lab/ColNetraEmbed") model = AutoModelForMultimodalLM.from_pretrained("Cognitive-Lab/ColNetraEmbed", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c03d584de42ca8a80af5c2da28b3b7e77afc0f27e5a3117725d999834181bae8
- Size of remote file:
- 8.6 GB
- SHA256:
- b709bc3be5562032e9261b64ed12bd558f745a77a34549c30be0728ca1090529
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