Text Classification
Transformers
PyTorch
English
roberta
fill-mask
fake-news
distilroberta
nlp
deep-learning
huggingface
fine-tuning
misinformation
text-embeddings-inference
Instructions to use YerayEsp/FakeBERTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YerayEsp/FakeBERTa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YerayEsp/FakeBERTa")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("YerayEsp/FakeBERTa") model = AutoModelForMaskedLM.from_pretrained("YerayEsp/FakeBERTa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2dc291a3cbce019c5b981cb5f5bc0ed453c17da930583cc434a9871df390f012
- Size of remote file:
- 329 MB
- SHA256:
- 7939dd3f2b45e2529430f554caaf903c1b8d9804492dfca8144c14dee12042cc
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