Instructions to use amengemeda/Fact-checking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amengemeda/Fact-checking with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="amengemeda/Fact-checking")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("amengemeda/Fact-checking") model = AutoModelForSequenceClassification.from_pretrained("amengemeda/Fact-checking", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 441c07a49d7d2c32a952fd96fbc1cadaf2a677ed4aad0f0c431d0a921d402cfb
- Size of remote file:
- 438 MB
- SHA256:
- 3e55bdad271b9a17ec4e657241c0684e79b77a9bddeccc5586c15ad012bf82f5
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