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
Update README.md
Browse files
README.md
CHANGED
|
@@ -13,7 +13,9 @@ language:
|
|
| 13 |
- it
|
| 14 |
library_name: transformers
|
| 15 |
widget:
|
| 16 |
-
- text:
|
|
|
|
|
|
|
| 17 |
---
|
| 18 |
|
| 19 |
### Abstract
|
|
|
|
| 13 |
- it
|
| 14 |
library_name: transformers
|
| 15 |
widget:
|
| 16 |
+
- text: Quando si apre la successione?
|
| 17 |
+
datasets:
|
| 18 |
+
- AndreaSimeri/Italian_Civil_Code
|
| 19 |
---
|
| 20 |
|
| 21 |
### Abstract
|