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-vit-b-16-inat-only with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- OpenCLIP
How to use imageomics/bioclip-vit-b-16-inat-only with OpenCLIP:
import open_clip model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms('hf-hub:imageomics/bioclip-vit-b-16-inat-only') tokenizer = open_clip.get_tokenizer('hf-hub:imageomics/bioclip-vit-b-16-inat-only') - Notebooks
- Google Colab
- Kaggle
Update README.md (#1)
Browse files- Update README.md (f1c8fda8c31f3bd798a0bf94deb8481b0e1f226b)
- Update README.md (8431dabd7c08026fb14913593d881e037b415222)
Co-authored-by: Balaji Radhakrishnan <balajiRRK@users.noreply.huggingface.co>
README.md
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- knowledge-guided
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datasets:
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- iNat21
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---
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- knowledge-guided
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datasets:
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- iNat21
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model_description: >-
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BioCLIP is a foundation model for the tree of life, built
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using CLIP architecture as a vision model for general organismal
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biology. This model is trained on iNat21 following the same procedure,
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however, iNat21 is a subset of the TreeOfLife-10M dataset on which
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BioCLIP was trained. More information can be found in the BioCLIP repository.
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