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
Download config.json from Gabrielkph/alias-mmbert-small: direct link, hf CLI and curl.
- Browser
- Download file 1.98 kB
-
https://huggingface.co/Gabrielkph/alias-mmbert-small/resolve/main/config.json
- Command line
-
hf download hf://Gabrielkph/alias-mmbert-small/config.json
-
curl -L -o config.json https://huggingface.co/Gabrielkph/alias-mmbert-small/resolve/main/config.json
1.98 kB
| { | |
| "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 | |
| } | |