Instructions to use rahon/product_name_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rahon/product_name_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rahon/product_name_classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rahon/product_name_classifier") model = AutoModelForSequenceClassification.from_pretrained("rahon/product_name_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from rahon/product_name_classifier: direct link, hf CLI and curl.
- Browser
- Download file 711 MB
-
https://huggingface.co/rahon/product_name_classifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://rahon/product_name_classifier/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/rahon/product_name_classifier/resolve/main/pytorch_model.bin
711 MB
- Xet hash:
- 2c50288dde32d1c42ae8dc96e9d071f6abcea9b3a679828bee6e6d67ef392eea
- Size of remote file:
- 711 MB
- SHA256:
- 44975bc95ea91305f729e34de65d73ddaf22ea1af0b81e2c85053e587e13edbc
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