---
license: mit
language:
- en
tags:
- histology
- pathology
- vision
- pytorch
- self-supervised
- vit
extra_gated_prompt: >-
  link https://huggingface.co/MahmoodLab/UNI
extra_gated_fields:
  Full name (first and last): text
  Current affiliation (no abbreviations): text
  Type of Affiliation:
    type: select
    options:
    - Academia
    - Industry
    - label: Other
      value: other
  Current and official institutional email (**this must match your primary email in your Hugging Face account, @gmail/@hotmail/@qq email domains will be denied**): text
  Please explain your intended research use: text
  I agree to all terms outlined above: checkbox
  I agree to use this model for non-commercial, academic purposes only: checkbox
  I agree not to distribute the model, if another user within your organization wishes to use the UNI model, they must register as an individual user: checkbox
metrics:
- accuracy
pipeline_tag: image-feature-extraction
library_name: timm
---

# Updates:
UNI2, a successor to UNI, trained on over 200 million images from over 350k diverse H&E and IHC slides has been released! Model weights and instructions are available at: \[[Huggingface Repo](https://huggingface.co/MahmoodLab/UNI2-h)\]

```
Works that use UNI should also attribute ViT and DINOv2.