Image Feature Extraction
timm
PyTorch
Safetensors
pathology
histology
medical imaging
self-supervised learning
vision transformer
foundation model
Instructions to use bioptimus/H-optimus-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use bioptimus/H-optimus-1 with timm:
import timm model = timm.create_model("hf_hub:bioptimus/H-optimus-1", pretrained=True) - Notebooks
- Google Colab
- Kaggle
Update HEST benchmark leaderboard
#20
by pauldoucet - opened
Dear Bioptimus team,
I would like to update the HEST benchmark official leaderboard with the performance results of H-optimus-1. I believe my access request was initially auto-rejected due to my current affiliation to Modella AI.
I confirm that I will only use the weights to replicate the benchmark results presented in the initial release
This thread was closed directly via email. Thanks.
ricardo-bioptimus changed discussion status to closed