Text Classification
Transformers
ONNX
Safetensors
English
modernbert
propaganda-detection
multi-label-classification
nci-protocol
text-embeddings-inference
Instructions to use synapti/nci-technique-classifier-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use synapti/nci-technique-classifier-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="synapti/nci-technique-classifier-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("synapti/nci-technique-classifier-v2") model = AutoModelForSequenceClassification.from_pretrained("synapti/nci-technique-classifier-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e4b02ff5c3f120ecbc62f62056aa496cd6eb5620941b020e81e4454785dff463
- Size of remote file:
- 5.91 kB
- SHA256:
- 1eca5c516bc6cde3a0789a0ce580ef2742352ab800c53b75cf9f1e1bb00b2591
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