Instructions to use kraftman1/image_ecommerce_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kraftman1/image_ecommerce_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="kraftman1/image_ecommerce_classifier") 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("kraftman1/image_ecommerce_classifier") model = AutoModelForImageClassification.from_pretrained("kraftman1/image_ecommerce_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from kraftman1/image_ecommerce_classifier: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/kraftman1/image_ecommerce_classifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://kraftman1/image_ecommerce_classifier/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kraftman1/image_ecommerce_classifier/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- 61dd15d52fbfb692a4dbfb3f0ca18d2cf7cbcca0a92bbbc44f387c194c3a49d3
- Size of remote file:
- 343 MB
- SHA256:
- 027aed54318ca8d9fbd1bcb9001e3c23fdf7c9a686e3f6f6773c1602099bd0cf
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