Text Classification
Transformers
PyTorch
roberta
Fake News Detection
Text Classification
text-embeddings-inference
Instructions to use vikram71198/distilroberta-base-finetuned-fake-news-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vikram71198/distilroberta-base-finetuned-fake-news-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vikram71198/distilroberta-base-finetuned-fake-news-detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vikram71198/distilroberta-base-finetuned-fake-news-detection") model = AutoModelForSequenceClassification.from_pretrained("vikram71198/distilroberta-base-finetuned-fake-news-detection") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
#3 opened almost 3 years ago
by
librarian-bot
Adding `safetensors` variant of this model
#2 opened about 3 years ago
by
SFconvertbot
Librarian Bot: Update dataset YAML metadata for model
#1 opened over 3 years ago
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librarian-bot