Instructions to use Yueh-Huan/news-category-classification-distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yueh-Huan/news-category-classification-distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Yueh-Huan/news-category-classification-distilbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Yueh-Huan/news-category-classification-distilbert") model = AutoModelForSequenceClassification.from_pretrained("Yueh-Huan/news-category-classification-distilbert") - Notebooks
- Google Colab
- Kaggle
distilbert-base-news-category-classification
This repository provides a distilbert model train on 210k news headlines from 2012 to 2022 from HuffPost. The model was trained by Yue
The training data can be found at the following Kaggle URL. https://www.kaggle.com/datasets/rmisra/news-category-dataset
Model and Project details: https://yueh-huan.com/posts/identify-news-category-based-on-news-headlines/
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