Text Classification
Transformers
Safetensors
modernbert
propaganda-detection
binary-classification
nci-protocol
text-embeddings-inference
Instructions to use synapti/nci-binary-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use synapti/nci-binary-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="synapti/nci-binary-detector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("synapti/nci-binary-detector") model = AutoModelForSequenceClassification.from_pretrained("synapti/nci-binary-detector") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a82886523d1e312cd1df7c536ae7192861ff67461ea4da789d7fafb59e8ed56
- Size of remote file:
- 1.2 GB
- SHA256:
- be1ab97a46359294ec6b5ffff2c8cad6f8fdc87bbf4fdc243126dddaa578a945
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