Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use caush/Clickbait2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use caush/Clickbait2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="caush/Clickbait2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("caush/Clickbait2") model = AutoModelForSequenceClassification.from_pretrained("caush/Clickbait2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c281b79a79845b8edcb93f8b67d8ad23de48328c4c6f8b787e624ab1c9175ec
- Size of remote file:
- 3.06 kB
- SHA256:
- 5360a7be4fa874a5ffbaf8434c1f065b1240930c454388ff192d5c79bd0d82f8
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