Instructions to use raoulmago/codice_fiscale with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use raoulmago/codice_fiscale with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="raoulmago/codice_fiscale")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("raoulmago/codice_fiscale") model = AutoModelForTokenClassification.from_pretrained("raoulmago/codice_fiscale", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "distilbert/distilbert-base-uncased", | |
| "activation": "gelu", | |
| "architectures": [ | |
| "DistilBertForTokenClassification" | |
| ], | |
| "attention_dropout": 0.1, | |
| "dim": 768, | |
| "dropout": 0.1, | |
| "hidden_dim": 3072, | |
| "id2label": { | |
| "0": "0", | |
| "1": "codice_fiscale", | |
| "2": "cognome", | |
| "3": "nome", | |
| "4": "comune_nascita", | |
| "5": "prov_nascita", | |
| "6": "data_nascita" | |
| }, | |
| "initializer_range": 0.02, | |
| "label2id": { | |
| "O": 0, | |
| "codice_fiscale": 1, | |
| "cognome": 2, | |
| "comune_nascita": 4, | |
| "data_nascita": 6, | |
| "nome": 3, | |
| "prov_nascita": 5 | |
| }, | |
| "max_position_embeddings": 512, | |
| "model_type": "distilbert", | |
| "n_heads": 12, | |
| "n_layers": 6, | |
| "pad_token_id": 0, | |
| "qa_dropout": 0.1, | |
| "seq_classif_dropout": 0.2, | |
| "sinusoidal_pos_embds": false, | |
| "tie_weights_": true, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.40.2", | |
| "vocab_size": 30522 | |
| } | |