Instructions to use Sifter/product-category-bert-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sifter/product-category-bert-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sifter/product-category-bert-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sifter/product-category-bert-classifier") model = AutoModelForSequenceClassification.from_pretrained("Sifter/product-category-bert-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sifter/product-category-bert-classifier: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/Sifter/product-category-bert-classifier/resolve/main/training_args.bin
- Command line
-
hf download hf://Sifter/product-category-bert-classifier/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/Sifter/product-category-bert-classifier/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- f6088c477ee77b20c342c84136437e700151d53fefcde125c3c8a7e9d38d99ea
- Size of remote file:
- 5.37 kB
- SHA256:
- 6c5dd732df51e5273c5b6da3bab8e4ab78827d75f5218b70cb8ab3275b430c3a
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