Token Classification
Transformers
ONNX
Safetensors
French
English
modernbert
pii
ner
anonymization
privacy
Instructions to use Gabrielkph/alias-mmbert-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gabrielkph/alias-mmbert-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Gabrielkph/alias-mmbert-small")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Gabrielkph/alias-mmbert-small") model = AutoModelForTokenClassification.from_pretrained("Gabrielkph/alias-mmbert-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,984 Bytes
850eab4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 | {
"architectures": [
"ModernBertForTokenClassification"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 2,
"classifier_activation": "gelu",
"classifier_bias": false,
"classifier_dropout": 0.0,
"classifier_pooling": "mean",
"cls_token_id": 1,
"decoder_bias": true,
"deterministic_flash_attn": false,
"dtype": "float32",
"embedding_dropout": 0.0,
"eos_token_id": 1,
"global_attn_every_n_layers": 3,
"global_rope_theta": 160000,
"gradient_checkpointing": false,
"hidden_activation": "gelu",
"hidden_size": 384,
"id2label": {
"0": "O",
"1": "B-PERSON",
"2": "I-PERSON",
"3": "B-ADDRESS",
"4": "I-ADDRESS",
"5": "B-EMAIL",
"6": "I-EMAIL",
"7": "B-PHONE",
"8": "I-PHONE",
"9": "B-IBAN",
"10": "I-IBAN",
"11": "B-NATIONAL_ID",
"12": "I-NATIONAL_ID",
"13": "B-BIRTH_DATE",
"14": "I-BIRTH_DATE",
"15": "B-IDENTIFIER",
"16": "I-IDENTIFIER"
},
"initializer_cutoff_factor": 2.0,
"initializer_range": 0.02,
"intermediate_size": 1152,
"label2id": {
"B-ADDRESS": 3,
"B-BIRTH_DATE": 13,
"B-EMAIL": 5,
"B-IBAN": 9,
"B-IDENTIFIER": 15,
"B-NATIONAL_ID": 11,
"B-PERSON": 1,
"B-PHONE": 7,
"I-ADDRESS": 4,
"I-BIRTH_DATE": 14,
"I-EMAIL": 6,
"I-IBAN": 10,
"I-IDENTIFIER": 16,
"I-NATIONAL_ID": 12,
"I-PERSON": 2,
"I-PHONE": 8,
"O": 0
},
"layer_norm_eps": 1e-05,
"local_attention": 128,
"local_rope_theta": 160000,
"mask_token_id": 4,
"max_position_embeddings": 8192,
"mlp_bias": false,
"mlp_dropout": 0.0,
"model_type": "modernbert",
"norm_bias": false,
"norm_eps": 1e-05,
"num_attention_heads": 6,
"num_hidden_layers": 22,
"pad_token_id": 0,
"position_embedding_type": "sans_pos",
"repad_logits_with_grad": false,
"sep_token_id": 1,
"sparse_pred_ignore_index": -100,
"sparse_prediction": false,
"transformers_version": "4.57.6",
"vocab_size": 256000
}
|