Text Classification
Transformers
TensorFlow
bert
generated_from_keras_callback
politics
agenda
issues
comparative agendas project
political communication
bills
laws
parliament
text-embeddings-inference
Instructions to use z-dickson/CAP_coded_US_Congressional_bills with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use z-dickson/CAP_coded_US_Congressional_bills with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="z-dickson/CAP_coded_US_Congressional_bills")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("z-dickson/CAP_coded_US_Congressional_bills") model = AutoModelForSequenceClassification.from_pretrained("z-dickson/CAP_coded_US_Congressional_bills", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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