Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use cnicu/product_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cnicu/product_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cnicu/product_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cnicu/product_classifier") model = AutoModelForSequenceClassification.from_pretrained("cnicu/product_classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bb5209c2a1155d047e7dd4f542fcf072bac038ddc0ad5e6d28bc54d6db885da3
- Size of remote file:
- 268 MB
- SHA256:
- d4f849b87defde93d24c85bf6ad06275e9b9cf091291cf5e1249eaccba6f0546
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