Instructions to use peng-lab/phoenix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use peng-lab/phoenix with timm:
import timm model = timm.create_model("hf_hub:peng-lab/phoenix", pretrained=True) - Notebooks
- Google Colab
- Kaggle
metadata
license: cc-by-nc-4.0
datasets:
- peng-lab/nest
language:
- en
- de
metrics:
- spearmanr
- pearsonr
- mse
base_model:
- bioptimus/H-optimus-1
- bioptimus/H0-mini
- MahmoodLab/UNI2-h
- paige-ai/Virchow2
pipeline_tag: zero-shot-classification
tags:
- spatial-transcriptomics
- histology
- pathology
library_name: timm