Text Classification
Transformers
PyTorch
Safetensors
English
distilbert
fake-news
sentence-classification
text-embeddings-inference
Instructions to use JosuMSC/fake-news-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JosuMSC/fake-news-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JosuMSC/fake-news-detector")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JosuMSC/fake-news-detector") model = AutoModelForSequenceClassification.from_pretrained("JosuMSC/fake-news-detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("JosuMSC/fake-news-detector")
model = AutoModelForSequenceClassification.from_pretrained("JosuMSC/fake-news-detector", device_map="auto")Quick Links
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JosuMSC/fake-news-detector")