Instructions to use Stremie/bert-base-uncased-clickbait with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Stremie/bert-base-uncased-clickbait with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Stremie/bert-base-uncased-clickbait")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Stremie/bert-base-uncased-clickbait") model = AutoModelForSequenceClassification.from_pretrained("Stremie/bert-base-uncased-clickbait", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 17134d8c33e385a44aec1bd7a8b7bc2037fcd25be6f9cad8c58ae57231e584b4
- Size of remote file:
- 438 MB
- SHA256:
- 558b9cc45267a5d453b4963e100876d6bbcce677613e285d24fa4cff268518b1
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