Feature Extraction
Transformers
Safetensors
English
qwen3_vl_text
medical
vision-encoder
radiology
ct
mri
x-ray
graph-rag
Instructions to use madrisight/madrimed1.2-text-embed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use madrisight/madrimed1.2-text-embed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="madrisight/madrimed1.2-text-embed")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("madrisight/madrimed1.2-text-embed") model = AutoModel.from_pretrained("madrisight/madrimed1.2-text-embed", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Medical Text Encoder - 2048-D
Madrimed 1.2 Vision Embed
Model Overview
It is published specifically for madrisight/madrimed1.2-vision-embed
Citation
@software{madrimed1.2-vision-embed,
title = {Madrimed 1.2 Vison Encoder},
author = {Madrisight},
year = {2026},
url = {https://huggingface.co/madrisight/madrimed1.2-vision-embed}
}
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