Token Classification
Transformers
ONNX
Safetensors
xlm-roberta
ner
on-device
privacy
flowx
openner
cross
de-identification
Instructions to use flowxai/piiguard with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowxai/piiguard with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="flowxai/piiguard")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("flowxai/piiguard") model = AutoModelForTokenClassification.from_pretrained("flowxai/piiguard", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_cross_attention": false, | |
| "architectures": [ | |
| "XLMRobertaForTokenClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": 0, | |
| "classifier_dropout": null, | |
| "dtype": "float32", | |
| "eos_token_id": 2, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "O", | |
| "1": "B-PERSON", | |
| "2": "I-PERSON", | |
| "3": "B-EMAIL", | |
| "4": "I-EMAIL", | |
| "5": "B-PHONE", | |
| "6": "I-PHONE", | |
| "7": "B-NATIONAL_ID", | |
| "8": "I-NATIONAL_ID", | |
| "9": "B-IBAN", | |
| "10": "I-IBAN", | |
| "11": "B-CARD", | |
| "12": "I-CARD", | |
| "13": "B-DATE", | |
| "14": "I-DATE" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "is_decoder": false, | |
| "label2id": { | |
| "B-CARD": 11, | |
| "B-DATE": 13, | |
| "B-EMAIL": 3, | |
| "B-IBAN": 9, | |
| "B-NATIONAL_ID": 7, | |
| "B-PERSON": 1, | |
| "B-PHONE": 5, | |
| "I-CARD": 12, | |
| "I-DATE": 14, | |
| "I-EMAIL": 4, | |
| "I-IBAN": 10, | |
| "I-NATIONAL_ID": 8, | |
| "I-PERSON": 2, | |
| "I-PHONE": 6, | |
| "O": 0 | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "max_position_embeddings": 514, | |
| "model_type": "xlm-roberta", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "output_past": true, | |
| "pad_token_id": 1, | |
| "position_embedding_type": "absolute", | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.14.1", | |
| "type_vocab_size": 1, | |
| "use_cache": false, | |
| "vocab_size": 250002 | |
| } | |