Feature Extraction
Transformers
PyTorch
clip
zero-shot-image-classification
vision
coin
coin-retrieval
coin-recognition
coin-search-engine
multi-modal learning
Instructions to use breezedeus/coin-clip-vit-base-patch32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use breezedeus/coin-clip-vit-base-patch32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="breezedeus/coin-clip-vit-base-patch32")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("breezedeus/coin-clip-vit-base-patch32") model = AutoModelForZeroShotImageClassification.from_pretrained("breezedeus/coin-clip-vit-base-patch32", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from breezedeus/coin-clip-vit-base-patch32: direct link, hf CLI and curl.
- Browser
- Download file 605 MB
-
https://huggingface.co/breezedeus/coin-clip-vit-base-patch32/resolve/27d73355b0260a2801723e8509af3dbfb3492ba1/pytorch_model.bin
- Command line
-
hf download hf://breezedeus/coin-clip-vit-base-patch32@27d73355b0260a2801723e8509af3dbfb3492ba1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/breezedeus/coin-clip-vit-base-patch32/resolve/27d73355b0260a2801723e8509af3dbfb3492ba1/pytorch_model.bin
605 MB
- Xet hash:
- 54353443fbb77ec1220de5d10bf4da364a9cad176c8ba20138ec219f49455cba
- Size of remote file:
- 605 MB
- SHA256:
- dec55ec4d28046e930bbf95e618ad842c9f4dfc5c9c6be8198d6f7adb5e3fd31
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