Instructions to use mmosko/Bert_Fake_News_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mmosko/Bert_Fake_News_Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mmosko/Bert_Fake_News_Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mmosko/Bert_Fake_News_Classification") model = AutoModelForSequenceClassification.from_pretrained("mmosko/Bert_Fake_News_Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7777e9e5b5fb9e50ee3a4211f9e55d0ce3f11002337a99729a17961ecee200f2
- Size of remote file:
- 5.37 kB
- SHA256:
- 17b444f8337e7af8db411ca019450a91abace41857fd18b7ad492cd0ac5d2c8e
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