models Virchow2 - Azure/azureml-assets GitHub Wiki

Virchow2

Overview

Virchow2 is a self-supervised vision transformer pretrained using 3.1M whole slide histopathology images. The model can be used as a tile-level feature extractor (frozen or finetuned) to achieve state-of-the-art results for a wide variety of downstream computational pathology use cases.

Model Details

Developed by: Paige, NYC, USA and Microsoft Research, Cambridge, MA USA Model Type: Image feature backbone Model Stats: Params (M): 632 Image size: 224 x 224 Model Architecture: Architecture: ViT-H/14 Patch size: 14 Layers: 32 Embedding dimension: 1280 Activation function: SwiGLU Attention heads: 16 LayerScale: true Register tokens: 4 Training Details: Precision: Mixed precision (fp16) Objective: Modified DINOv2 (https://doi.org/10.48550/arXiv.2304.07193) KoLeo regularizer replaced with kernel density estimator Crop-and-resize augmentation replaced with extended context translation Paper: Virchow2: Scaling Self-Supervised Mixed Magnification Models in Pathology https://arxiv.org/pdf/2408.00738 Pretraining Dataset: Internal dataset of 3.1 million whole slide images from Memorial Sloan Kettering Cancer Center, tiles sampled at 2.0, 1.0, 0.5 and 0.25 microns per pixel resolution (5x, 10x, 20x, and 40x magnification). License: CC-BY-NC-ND-4.0

Model Usage

Direct use Virchow2 intended to be used as a frozen feature extractor as the foundation for tile-level and whole slide-level classifiers.

Downstream use Virchow2 can be finetuned to adapt to specific tasks and/or datasets.

Terms of use

The Virchow2 Model and associated code are released under the CC-BY-NC-ND 4.0 license and may only be used for non-commercial, academic research purposes with proper attribution. Any commercial use, sale, or other monetization of the Virchow2 Model and its derivatives, which include models trained on outputs from the Virchow2 Model or datasets created from the Virchow2 Model, is prohibited and requires prior approval. By downloading /deploying the Virchow2 Model, you attest that all account information (affiliation, research use) is correct and up-to-date. By downloading/deploying the Virchow2 Model, you agree not to distribute, publish or reproduce a copy of the Virchow2 Model. If another user within your organization wishes to use the Virchow2 Model, they must register as an individual user and agree to comply with these terms of use. If you are a commercial entity, please contact the corresponding author. Further, by downloading/deploying the Virchow2 Model, you agree you will only use the Virchow2 Model for academic research purposes and will not use, or allow others to use, the Virchow2 Model to:

  1. Diagnose, cure, mitigate, treat, or prevent disease or any other conditions, including for Investigational Use Only (“IUO”), Research Use Only (“RUO”), commercial, clinical or other similar use, and including as a substitute for professional medical advice, a healthcare opinion, a diagnosis, treatment, or the clinical judgment of a healthcare professional, as no license or right is granted for any such purposes.
  2. Re-identify the deidentified data used to develop the Virchow2 Model;
  3. Violate the law or others’ rights, including to: a. Engage in, promote, generate, contribute to, encourage, plan, incite, or further illegal or unlawful activity or content; b. Engage in, promote, incite, or facilitate the harassment, abuse, threatening, or bullying of individuals or groups of individuals; c. Engage in, promote, incite, or facilitate discrimination or other unlawful or harmful conduct in the provision of employment, employment benefits, credit, housing, other economic benefits, or other essential goods and services; d. Engage in the unauthorized or unlicensed practice of any profession including, but not limited to, financial, legal, medical/health, or related professional practices; e. Collect, process, disclose, generate, or infer the identity of individuals or the health, demographic, or other sensitive personal or private information about individuals without rights and consents required by applicable laws; f. Engage in or facilitate any action or generate any content that infringes, misappropriates, or otherwise violates any third-party rights, including the outputs or results of any products or services using the Virchow2 Model or any related materials; and g. Create, generate, or facilitate the creation of malicious code, malware, computer viruses or do anything else that could disable, overburden, interfere with or impair the proper working, integrity, operation or appearance of a website or computer system.
  4. Engage in, promote, incite, facilitate, or assist in the planning or development of activities that present a risk of death or bodily harm to individuals, including the use of the Virchow2 Model as a medical device, clinical support, diagnostic tool, or other technology intended to be used in the diagnosis, cure, mitigation, treatment, or prevention of disease or other conditions, including for Investigational Use Only (“IUO”), Research Use Only (“RUO”), commercial, clinical or similar use; and
  5. Intentionally deceive or mislead others, including representing that the use of the Virchow2 Model or its outputs is human-generated. Further, you agree that you will appropriately disclose to end users any known dangers of your AI system.

Citation

Please cite the following work if you used this model in your research.

Zimmermann, E., Vorontsov, E., Viret, J. et al. Virchow2: Scaling Self-Supervised Mixed Magnification Models in Pathology. arXiv preprint arXiv:2408.00738 (2024).

@article{zimmermann2024virchow2,
  title={Virchow2: Scaling Self-Supervised Mixed Magnification Models in Pathology}, 
  author={Eric Zimmermann and Eugene Vorontsov and Julian Viret and Adam Casson and Michal Zelechowski and George Shaikovski and Neil Tenenholtz and James Hall and Thomas Fuchs and Nicolo Fusi and Siqi Liu and Kristen Severson},
  journal={arXiv preprint arXiv:2408.00738},
  year={2024},
}

Disclaimer Virchow2 has been developed for research purposes and is not intended for diagnosis of real patients or projection/prediction of future disease possibilities.

Fairness evaluation cannot be completed due to limitations in the metadata. Underlying biases of the training datasets may not be well characterized and may not be representative of all demographics.

Sample Input and Output (for real-time inference)

Sample Input

{
  "input_data": {
    "columns": [
      "image"
    ],
    "index":[0],
    "data": [
      ["image1"]
   ]
 }
}

Note:

  • "image1" and "image2" should be publicly accessible urls or strings in base64 format.

Sample Output

[
  {
    "output": [
      0.0, 0.0, 0.0, 0.0
    ]
  }
]

Output will be image embeddings.

Version: 3

Tags

task : image-feature-extraction industry : health-and-life-sciences Preview inference_supported_envs : ['hf'] license : custom `licenseDescription : PAIGE.AI, INC. EMBEDDING SERVICES TERMS OF USE Updated as of November 11, 2025 These terms of use (the “Terms of Use”) are between Paige.AI, Inc. and its affiliates (collectively, “Paige”, “us”, “we”, or “our”) and you and/or the entity or organization you represent. By accessing or using the Embeddings Service (defined below), you agree to be legally bound by these Terms of Use. If you do not accept these Terms of Use, do not use the Embeddings Service. You are representing that you are lawfully able to enter into contracts (e.g., you are not a minor) and have the capacity and authority to enter into these Terms of Use. If you are entering into these Terms of Use for an entity, such as the company you work for, you represent that you have authority to bind that entity. You agree that “you”, “your” or “user” as used in these Terms of Use includes you, personally, and, if applicable, any entity you represent. We reserve the right to change these Terms of Use from time to time for any reason, which shall be affected by posting the updated Terms of Use here. Your continued use of the Embeddings Services after any changes are posted constitutes your acceptance of the new Terms of Use. Arbitration THESE TERMS OF USE CONTAIN A MANDATORY INDIVIDUAL ARBITRATION AND CLASS ACTION/JURY TRIAL WAIVER PROVISION THAT REQUIRES THE USE OF ARBITRATION ON AN INDIVIDUAL BASIS TO RESOLVE DISPUTES, RATHER THAN JURY TRIALS OR CLASS ACTIONS. You agree to resolve disputes through binding arbitration, mediation, or small claims court instead of in courts of general jurisdiction. If you initiate an arbitration in which you seek more than $75,000 in damages, the payment of attorneys’ fees will be governed by the AAA Rules (as defined below). Any arbitration under these Terms of Use will take place on an individual basis; class arbitrations and class actions are not permitted.

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You agree that the Terms of Use shall be interpreted and construed in accordance with the laws of the State of Delaware without regard to its choice of law principles. You agree that any disagreements, disputes or claims arising under or relating to these Terms of Use shall be referred to and finally resolved by arbitration under the commercial arbitration rules of the Judicial Arbitration and Mediation Services Inc. (“JAMS”). The seat of the arbitration shall be New York, NY. The language to be used in the arbitration shall be English. The arbitration shall be conducted by one arbitrator selected jointly by you and Paige or, if we cannot agree on an arbitrator, by the President, or his or her designee, of the International Chamber of Commerce. The decision of the arbitrator shall be binding. The decision of the arbitrator shall be executory, and judgment thereon may be entered by any court of competent jurisdiction. YOU HEREBY IRREVOCABLY WAIVE, TO THE FULLEST EXTENT PERMITTED BY APPLICABLE LAW, ANY AND ALL RIGHT TO A TRIAL BY JURY IN ANY LEGAL PROCEEDING ARISING OUT OF OR RELATING TO THESE TERMS OF USE. # 15. Miscellaneous. You may not delegate, assign or transfer these Terms of Use or any of its rights and obligations hereunder and any attempt to do so shall be void. Paige may assign all of its rights and obligations under these Terms of Use at any time. The rights and obligations of Paige under these Terms of Use shall inure to the benefit and shall be binding upon the successor and assigns of Paige and/or its assets. Paige and you are independent contractors and are not partners, joint venturers, agents, employees or representatives of the other party. These Terms of Use shall continue to apply with respect to any access or use you have made of the Embeddings Service even after such access or use terminates. Paige reserves the right, in its sole discretion, to restrict, suspend and/or terminate your access to all or any part of the Embeddings Service at any time without prior notice or liability for any reason or no reason. Paige may change, suspend, discontinue or disable all or any aspect of the Embeddings Service at any time, including the availability of any feature, database, or service, without prior notice or liability. Paige is not liable for delays or outages caused by events beyond its reasonable control. These Terms of Use together with any Microsoft agreement or any Paige addenda shall constitute the entire agreement regarding the Embedding Service. If you have any questions about these Terms of Use, please contact [email protected]

If you have any questions about these Terms of Use, please contact [email protected] author : Paige hiddenlayerscanned SharedComputeCapacityEnabled inference_compute_allow_list : ['Standard_NC6s_v3', 'Standard_NC12s_v3', 'Standard_NC24s_v3', 'Standard_NC24ads_A100_v4', 'Standard_NC48ads_A100_v4', 'Standard_NC96ads_A100_v4', 'Standard_ND96asr_v4', 'Standard_ND96amsr_A100_v4', 'Standard_ND40rs_v2']`

View in Studio: https://ml.azure.com/registries/azureml/models/Virchow2/version/3

License: custom

Properties

inference-min-sku-spec: 6|1|112|64

inference-recommended-sku: Standard_NC6s_v3, Standard_NC12s_v3, Standard_NC24s_v3, Standard_NC24ads_A100_v4, Standard_NC48ads_A100_v4, Standard_NC96ads_A100_v4, Standard_ND96asr_v4, Standard_ND96amsr_A100_v4, Standard_ND40rs_v2

languages: en

SharedComputeCapacityEnabled: True

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