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:
- 12d519642d14fd17c2549d06ad3d2f71e8f1f5cbdc9aa7226a6df6bb0b9bc298
- Size of remote file:
- 1.38 kB
- SHA256:
- 78a1d1a5c8df0ff87f3d9a923fa98aa9b5f51a25e6518dd0f5b32d02e9a66dfd
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