Token Classification
Transformers
Safetensors
Ukrainian
roberta
ner
named-entity-recognition
pii
pii-detection
personal-data
anonymization
pseudonymization
de-identification
data-privacy
privacy
redaction
legal
legal-nlp
court-decisions
ukrainian
ukraine
synthetic-data
Eval Results (legacy)
Instructions to use davidmelash/wechsel_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davidmelash/wechsel_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="davidmelash/wechsel_base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("davidmelash/wechsel_base") model = AutoModelForTokenClassification.from_pretrained("davidmelash/wechsel_base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,691 Bytes
db4c341 | 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 | {
"add_cross_attention": false,
"architectures": [
"RobertaForTokenClassification"
],
"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-\u041e\u0421\u041e\u0411\u0410",
"2": "I-\u041e\u0421\u041e\u0411\u0410",
"3": "B-\u0410\u0414\u0420\u0415\u0421\u0410",
"4": "I-\u0410\u0414\u0420\u0415\u0421\u0410",
"5": "B-\u041d\u041e\u041c\u0415\u0420",
"6": "I-\u041d\u041e\u041c\u0415\u0420",
"7": "B-\u0406\u041d\u0424\u041e\u0420\u041c\u0410\u0426\u0406\u042f",
"8": "I-\u0406\u041d\u0424\u041e\u0420\u041c\u0410\u0426\u0406\u042f"
},
"initializer_range": 0.02,
"intermediate_size": 3072,
"is_decoder": false,
"label2id": {
"B-\u0406\u041d\u0424\u041e\u0420\u041c\u0410\u0426\u0406\u042f": 7,
"B-\u0410\u0414\u0420\u0415\u0421\u0410": 3,
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"I-\u041d\u041e\u041c\u0415\u0420": 6,
"I-\u041e\u0421\u041e\u0411\u0410": 2,
"O": 0
},
"layer_norm_eps": 1e-05,
"max_position_embeddings": 514,
"model_type": "roberta",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"pad_token_id": 1,
"position_embedding_type": "absolute",
"pseudo_stride": 128,
"pseudo_window": 512,
"tie_word_embeddings": true,
"transformers_version": "5.18.0",
"type_vocab_size": 1,
"use_cache": false,
"vocab_size": 50265
}
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