Text Classification
Transformers
Safetensors
modernbert
regression
legal
locus
text-embeddings-inference
Instructions to use LocalLaws/LOCUS-Enforcement-Discretion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LocalLaws/LOCUS-Enforcement-Discretion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LocalLaws/LOCUS-Enforcement-Discretion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LocalLaws/LOCUS-Enforcement-Discretion") model = AutoModelForSequenceClassification.from_pretrained("LocalLaws/LOCUS-Enforcement-Discretion") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a6ae848df80a61a2304c95438567551d5d19ff2af41b3e799f3772092d1bce4a
- Size of remote file:
- 5.78 kB
- SHA256:
- 74318fff555ad5139731b385f6d0014f9039f81871cca2f2e6e5f868c48f5da4
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