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:
# pip install -U transformers accelerate # 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
Download preprocessor_config.json from Cognitive-Lab/ColNetraEmbed: direct link, hf CLI and curl.
- Browser
- Download file 570 Bytes
-
https://huggingface.co/Cognitive-Lab/ColNetraEmbed/resolve/56d5d23db592b285b412bcfaf32ff0df54498fa8/preprocessor_config.json
- Command line
-
hf download hf://Cognitive-Lab/ColNetraEmbed@56d5d23db592b285b412bcfaf32ff0df54498fa8/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/Cognitive-Lab/ColNetraEmbed/resolve/56d5d23db592b285b412bcfaf32ff0df54498fa8/preprocessor_config.json
570 Bytes
| { | |
| "do_convert_rgb": null, | |
| "do_normalize": true, | |
| "do_pan_and_scan": null, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "Gemma3ImageProcessor", | |
| "image_seq_length": 256, | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "pan_and_scan_max_num_crops": null, | |
| "pan_and_scan_min_crop_size": null, | |
| "pan_and_scan_min_ratio_to_activate": null, | |
| "processor_class": "Gemma3Processor", | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 896, | |
| "width": 896 | |
| } | |
| } | |