Zero-Shot Image Classification
Transformers
PyTorch
English
clip
geolocalization
geolocation
geographic
street
climate
urban
rural
multi-modal
geoguessr
Instructions to use geolocal/StreetCLIP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use geolocal/StreetCLIP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="geolocal/StreetCLIP") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("geolocal/StreetCLIP") model = AutoModelForZeroShotImageClassification.from_pretrained("geolocal/StreetCLIP") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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version https://git-lfs.github.com/spec/v1
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oid sha256:66a260a44a9f6ed735ccbc0c035c3db984ec39b2f3d726b7d6f7d6580525fb50
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size 1711853860
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