Zero-Shot Image Classification
OpenCLIP
Safetensors
English
biology
CV
images
imageomics
clip
species-classification
biological visual task
multimodal
animals
plants
fungi
species
taxonomy
rare species
endangered species
evolutionary biology
knowledge-guided
Instructions to use imageomics/bioclip-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- OpenCLIP
How to use imageomics/bioclip-2 with OpenCLIP:
import open_clip model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms('hf-hub:imageomics/bioclip-2') tokenizer = open_clip.get_tokenizer('hf-hub:imageomics/bioclip-2') - Notebooks
- Google Colab
- Kaggle
Add descriptions to `yaml`
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by egrace479 - opened
README.md
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language:
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- en
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library_name: open_clip
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tags:
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- biology
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- CV
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language:
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- en
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library_name: open_clip
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model_name: "BioCLIP 2"
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model_description: "Foundation model for biology organismal images. It is trained on TreeOfLife-200M on the basis of a CLIP model (ViT-14/L) pre-trained on LAION-2B. BioCLIP 2 yields state-of-the-art performance in recognizing various species. More importantly, it demonstrates emergent properties beyond species classification after extensive hierarchical contrastive training."
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tags:
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- biology
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- CV
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