Instructions to use shahukareem/coral-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shahukareem/coral-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="shahukareem/coral-classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("shahukareem/coral-classification") model = AutoModelForImageClassification.from_pretrained("shahukareem/coral-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from shahukareem/coral-classification: direct link, hf CLI and curl.
- Browser
- Download file 347 MB
-
https://huggingface.co/shahukareem/coral-classification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://shahukareem/coral-classification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/shahukareem/coral-classification/resolve/main/pytorch_model.bin
347 MB
- Xet hash:
- 2aea7c6449e7a5095d3fd1d2b42836d03534ff050c650cfe48846691defbc746
- Size of remote file:
- 347 MB
- SHA256:
- f600e910ecce023919565ac699c4b728cdd1a5c4cef148f7bdcec02ead1f1548
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