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 training_args.bin from kraftman1/image_ecommerce_classifier: direct link, hf CLI and curl.
- Browser
- Download file 3.64 kB
-
https://huggingface.co/kraftman1/image_ecommerce_classifier/resolve/main/training_args.bin
- Command line
-
hf download hf://kraftman1/image_ecommerce_classifier/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/kraftman1/image_ecommerce_classifier/resolve/main/training_args.bin
3.64 kB
- Xet hash:
- 858fd8dd20553486e0cbb997ffae38c0e48150395042b4f9ee85cf17e3ee29c3
- Size of remote file:
- 3.64 kB
- SHA256:
- 6b22019b1653db2483cfe9cd9ac7facd9fa8bb1f07e7c2868b3bc17fd54661b3
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