Zero-Shot Image Classification
OpenCLIP
English
clip
biology
CV
images
animals
species
taxonomy
rare species
endangered species
evolutionary biology
multimodal
knowledge-guided
Instructions to use imageomics/bioclip with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- OpenCLIP
How to use imageomics/bioclip with OpenCLIP:
import open_clip model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms('hf-hub:imageomics/bioclip') tokenizer = open_clip.get_tokenizer('hf-hub:imageomics/bioclip') - Notebooks
- Google Colab
- Kaggle
Easy evaluation of the zero-shot capabilities of bioclip
#4
by fhvilshoj - opened
Hi!
Thanks for your big efforts in training this model. It's truly helping push forward the field of AI!
I wanted to show how we've evaluated the model against a bunch of others on a handful of medical datasets.
We did it with this repo: https://github.com/encord-team/text-to-image-eval
Would be curious to hear how this stacks up against your findings!
