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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "cls_token": "[CLS]", | |
| "mask_token": "[MASK]", | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "unk_token": "[UNK]" | |
| } | |