Instructions to use dl4ds/herbaria_foundation_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dl4ds/herbaria_foundation_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="dl4ds/herbaria_foundation_model") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("dl4ds/herbaria_foundation_model") model = AutoModelForZeroShotImageClassification.from_pretrained("dl4ds/herbaria_foundation_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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lowest loss model (#2)
Verified signature- Lowest loss (0.081) model - kaggle 2022 data (388f69a32c0e4558a22b0a4ce70b7c021e92bc84)e72925b
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new_model (#1)
Verified signature- Epoch 1 new model - kaggle 2022 data (b3f0b0b8378b1feafc236d3a7aeda8bf2d9e3e66)de612d6
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Initial README.md template
Verified signatureCreated a template based on the CLIP model card at https://huggingface.co/openai/clip-vit-base-patch32/edit/main/README.md.fe0b7c0 -
initial commit
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