Instructions to use Shadman-Rohan/FakevsRealNews with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shadman-Rohan/FakevsRealNews with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Shadman-Rohan/FakevsRealNews")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Shadman-Rohan/FakevsRealNews") model = AutoModelForSequenceClassification.from_pretrained("Shadman-Rohan/FakevsRealNews") - Notebooks
- Google Colab
- Kaggle
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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#
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The challenge involved building a fake news classifier using the huggingface library.
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This final model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an fake-and-real-news dataset. The link to the dataset is https://www.kaggle.com/datasets/clmentbisaillon/fake-and-real-news-dataset.
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# Coding challenge
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The challenge involved building a fake news classifier using the huggingface library.
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This final model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an fake-and-real-news dataset. The link to the dataset is https://www.kaggle.com/datasets/clmentbisaillon/fake-and-real-news-dataset.
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