Text Classification
Transformers
Safetensors
modernbert
democracy
political-science
party-competition
democratic-rhetoric
mmBert
text-embeddings-inference
Instructions to use LBenoit/democracy-mmBert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LBenoit/democracy-mmBert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LBenoit/democracy-mmBert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LBenoit/democracy-mmBert") model = AutoModelForSequenceClassification.from_pretrained("LBenoit/democracy-mmBert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b23358e5d61bbf1a3dece7580665243edf9fc14d02b89e0d02a0bc363cfedb0f
- Size of remote file:
- 34.4 MB
- SHA256:
- 07ad7cc435dcd5ea10fa3cb7c8bed1ae54c083a8dd49f48a4b31834c86957972
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