Text Classification
Transformers
PyTorch
English
bert
deep learning
law article retrieval
natural language processing
BERT
information retrieval
legal ai
legal bert
gdpr
general data protection regulation
text-embeddings-inference
Instructions to use AndreaSimeri/LegalBERT_GDPR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AndreaSimeri/LegalBERT_GDPR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AndreaSimeri/LegalBERT_GDPR")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AndreaSimeri/LegalBERT_GDPR") model = AutoModelForSequenceClassification.from_pretrained("AndreaSimeri/LegalBERT_GDPR") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 21d89e35307cecca13fafd7080cc2750aee01d5cdc5729f80bb2ba1f7e2868a6
- Size of remote file:
- 438 MB
- SHA256:
- b5ba32c9f4b7c5fd576bdd7686703b5f45e2960049bf15d094954aae419dcbe7
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