Instructions to use VSPuzzler/SemevalClickbaitSpoilingNew with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VSPuzzler/SemevalClickbaitSpoilingNew with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="VSPuzzler/SemevalClickbaitSpoilingNew")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("VSPuzzler/SemevalClickbaitSpoilingNew") model = AutoModelForSequenceClassification.from_pretrained("VSPuzzler/SemevalClickbaitSpoilingNew", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from VSPuzzler/SemevalClickbaitSpoilingNew: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/VSPuzzler/SemevalClickbaitSpoilingNew/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://VSPuzzler/SemevalClickbaitSpoilingNew@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/VSPuzzler/SemevalClickbaitSpoilingNew/resolve/refs%2Fpr%2F1/pytorch_model.bin
268 MB
- Xet hash:
- 157e8f0d378011b598107779ae52ca27d29f370030d93fae05ba1213fb11612e
- Size of remote file:
- 268 MB
- SHA256:
- 1e0245e6591a24422073905214bcbe73098b2f73a6d8ca6a40b32c136ffaf21e
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