Instructions to use AtomicoLabs/ALF-pii-nano with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AtomicoLabs/ALF-pii-nano with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="AtomicoLabs/ALF-pii-nano")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("AtomicoLabs/ALF-pii-nano") model = AutoModelForTokenClassification.from_pretrained("AtomicoLabs/ALF-pii-nano", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "DebertaV2ForTokenClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": 1, | |
| "dtype": "float32", | |
| "eos_token_id": 2, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 384, | |
| "id2label": { | |
| "0": "O", | |
| "1": "B-ACCOUNT_IBAN", | |
| "2": "B-ADDRESS", | |
| "3": "B-CREDIT_CARD", | |
| "4": "B-DATE_DOB", | |
| "5": "B-EMAIL", | |
| "6": "B-ID_NUMBER", | |
| "7": "B-IP", | |
| "8": "B-ORG", | |
| "9": "B-PERSON", | |
| "10": "B-PHONE", | |
| "11": "B-USERNAME_URL", | |
| "12": "I-ACCOUNT_IBAN", | |
| "13": "I-ADDRESS", | |
| "14": "I-CREDIT_CARD", | |
| "15": "I-DATE_DOB", | |
| "16": "I-EMAIL", | |
| "17": "I-ID_NUMBER", | |
| "18": "I-IP", | |
| "19": "I-ORG", | |
| "20": "I-PERSON", | |
| "21": "I-PHONE", | |
| "22": "I-USERNAME_URL" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 1536, | |
| "label2id": { | |
| "B-ACCOUNT_IBAN": 1, | |
| "B-ADDRESS": 2, | |
| "B-CREDIT_CARD": 3, | |
| "B-DATE_DOB": 4, | |
| "B-EMAIL": 5, | |
| "B-ID_NUMBER": 6, | |
| "B-IP": 7, | |
| "B-ORG": 8, | |
| "B-PERSON": 9, | |
| "B-PHONE": 10, | |
| "B-USERNAME_URL": 11, | |
| "I-ACCOUNT_IBAN": 12, | |
| "I-ADDRESS": 13, | |
| "I-CREDIT_CARD": 14, | |
| "I-DATE_DOB": 15, | |
| "I-EMAIL": 16, | |
| "I-ID_NUMBER": 17, | |
| "I-IP": 18, | |
| "I-ORG": 19, | |
| "I-PERSON": 20, | |
| "I-PHONE": 21, | |
| "I-USERNAME_URL": 22, | |
| "O": 0 | |
| }, | |
| "layer_norm_eps": 1e-07, | |
| "legacy": true, | |
| "max_position_embeddings": 512, | |
| "max_relative_positions": -1, | |
| "model_type": "deberta-v2", | |
| "norm_rel_ebd": "layer_norm", | |
| "num_attention_heads": 6, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 0, | |
| "pooler_dropout": 0.0, | |
| "pooler_hidden_act": "gelu", | |
| "pooler_hidden_size": 384, | |
| "pos_att_type": [ | |
| "p2c", | |
| "c2p" | |
| ], | |
| "position_biased_input": false, | |
| "position_buckets": 256, | |
| "relative_attention": true, | |
| "share_att_key": true, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.5.4", | |
| "type_vocab_size": 0, | |
| "use_cache": false, | |
| "vocab_size": 128100 | |
| } | |