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
Request for model access
#12
by momorxy - opened
I am writing to formally request access to your model, H-Optimus-1. I am contacting you from my institutional email address and intend to use the model strictly for academic research purposes. Specifically, I plan to evaluate H-Optimus-1 alongside other foundation models in weakly supervised classification tasks on WSI data.
Thank you very much for your time and consideration. I look forward to the opportunity to include this model in our comparative analysis, which I believe will contribute meaningful insights to our research.
Hi @momorxy , thanks for the follow-up. Closing the thread as your access request has been reviewed and granted. Thanks.
ricardo-bioptimus changed discussion status to closed