Model Card for CONCHv1_5

What is CONCHv1_5?

CONCHv1_5 is based on the CONCH model, a vision-language model pretrained on 1.17 image/captions in histopathology. CONCHv1_5 is based on a Vision Transformer Large (ViT-L) model restored from the UNI checkpoint, and fine-tuned in a similar fashion as CONCH.

Requesting Access

As mentioned in the gated prompt, you must agree to the outlined terms of use, with the primary email for your HuggingFace account matching your institutional email. If your primary email is a personal email (@gmail/@hotmail/@qq) your request will be denied. To fix this, you can: (1) add your official institutional email to your HF account, and confirm your email address to verify, and (2) set your institutional email as your primary email in your HF account. Other reasons for your request access being denied include other mistakes in the form submitted, for example: full name includes abbreviations, affiliation is not spelled out, the described research use is not sufficient, or email domain address not recognized.

Model Description

• Developed by: Mahmood Lab AI for Pathology @ Harvard/BWH
• Model type: Vision backbone (ViT-L/16) trained using CoCa
• Pretraining dataset: 1.17 image/caption pairs in histopathology
• Repository: TBD
• Paper: TBD
• License: CC-BY-NC-ND-4.0

License and Terms of Use

This 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 CONCHv1_5 model and its derivatives, which include models trained on outputs from the CONCHv1_5 model or datasets created from the CONCHv1_5 model, is prohibited and requires prior approval. Downloading the model requires prior registration on Hugging Face and agreeing to the terms of use. By downloading this model, you agree not to distribute, publish or reproduce a copy of the model. If another user within your organization wishes to use the CONCH_v1_5 model, they must register as an individual user and agree to comply with the terms of use. Users may not attempt to re-identify the deidentified data used to develop the underlying model. If you are a commercial entity, please contact the corresponding author.

Contact

For any additional questions or comments, contact Faisal Mahmood (faisalmahmood@bwh.harvard.edu), or Ming Y. Lu (mlu16@bwh.harvard.edu).