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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: \[[Huggingface Repo](https://huggingface.co/MahmoodLab/UNI2-h)\]
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Works that use UNI should also attribute ViT and DINOv2. |