Instructions to use flatmoon102/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flatmoon102/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="flatmoon102/image_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("flatmoon102/image_classification") model = AutoModelForImageClassification.from_pretrained("flatmoon102/image_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from flatmoon102/image_classification: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/flatmoon102/image_classification/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://flatmoon102/image_classification@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/flatmoon102/image_classification/resolve/refs%2Fpr%2F1/pytorch_model.bin
343 MB
- Xet hash:
- 8b2e22bb6f74800d67e4c9d5cdeec27ed086929c754b9e730ed2ad7320f6c528
- Size of remote file:
- 343 MB
- SHA256:
- 29f0cd5225f559ea386df434bdc4c3de35626bec9f8f6ae255568c20a13e5dae
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