Text Classification
Transformers
TensorFlow
ONNX
German
bert
generated_from_keras_callback
text-embeddings-inference
Instructions to use ml-projects/clickbait-ml_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ml-projects/clickbait-ml_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ml-projects/clickbait-ml_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ml-projects/clickbait-ml_bert") model = AutoModelForSequenceClassification.from_pretrained("ml-projects/clickbait-ml_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac1376e59be98e47eb5c4eadf9e8ba65e48d9c365164dc4895153c287f91e799
- Size of remote file:
- 437 MB
- SHA256:
- e278be0b397fefea7acd096a7acdd488e8a5e1f0a96f8fdb552d279e0f82c08e
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