Text Classification
Transformers
PyTorch
Italian
bert
deep learning
law article retrieval
natural language processing
BERT
information retrieval
legal ai
italian civil code
text-embeddings-inference
Instructions to use AndreaSimeri/LamBERTa_v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AndreaSimeri/LamBERTa_v5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AndreaSimeri/LamBERTa_v5")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AndreaSimeri/LamBERTa_v5") model = AutoModelForSequenceClassification.from_pretrained("AndreaSimeri/LamBERTa_v5") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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oid sha256:112e4244d2a988e82b97e24229ea7d014fe39f793d64a112392c9b17941fe54e
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