Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use caush/Clickbait1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use caush/Clickbait1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="caush/Clickbait1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("caush/Clickbait1") model = AutoModelForSequenceClassification.from_pretrained("caush/Clickbait1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3e31d07091f166e5ff685df03921bf4177b0d18dda83ce255becb1c4ac31db5b
- Size of remote file:
- 471 MB
- SHA256:
- cb3974d0f5dfb3facdbd8013f682b752582fb15f271ba8c9b06a373a6fb2aeb4
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