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
- Xet hash:
- f8ac2448597fd5128cc4cc572bfec94a31695831113a1a171e409842c7874c50
- Size of remote file:
- 1.71 GB
- SHA256:
- cf6dc3802a8bf9301560b1aa0cd1fa983b4139f96a1befc43802e387401fe6c0
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