Token Classification
Transformers
Safetensors
Turkish
privacy_filter
privacy
pii
kvkk
turkish
named-entity-recognition
data-redaction
privacy-filter
runeward
Instructions to use curiositytech/runeward-kvkk-filter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use curiositytech/runeward-kvkk-filter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="curiositytech/runeward-kvkk-filter")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("curiositytech/runeward-kvkk-filter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "bidirectional_context": true, | |
| "bidirectional_left_context": 128, | |
| "bidirectional_right_context": 128, | |
| "category_version": "kvkk_tr_v1", | |
| "default_n_ctx": 128000, | |
| "encoding": "o200k_base", | |
| "experts_per_token": 4, | |
| "head_dim": 64, | |
| "hidden_size": 640, | |
| "inference_contract_version": 1, | |
| "initial_context_length": 4096, | |
| "intermediate_size": 640, | |
| "max_position_embeddings": 131072, | |
| "model_type": "privacy_filter", | |
| "ner_class_names": [ | |
| "O", | |
| "B-private_person", | |
| "I-private_person", | |
| "E-private_person", | |
| "S-private_person", | |
| "B-private_email", | |
| "I-private_email", | |
| "E-private_email", | |
| "S-private_email", | |
| "B-private_phone", | |
| "I-private_phone", | |
| "E-private_phone", | |
| "S-private_phone", | |
| "B-private_address", | |
| "I-private_address", | |
| "E-private_address", | |
| "S-private_address", | |
| "B-private_date", | |
| "I-private_date", | |
| "E-private_date", | |
| "S-private_date", | |
| "B-private_url", | |
| "I-private_url", | |
| "E-private_url", | |
| "S-private_url", | |
| "B-account_number", | |
| "I-account_number", | |
| "E-account_number", | |
| "S-account_number", | |
| "B-secret", | |
| "I-secret", | |
| "E-secret", | |
| "S-secret", | |
| "B-tckn", | |
| "I-tckn", | |
| "E-tckn", | |
| "S-tckn", | |
| "B-iban", | |
| "I-iban", | |
| "E-iban", | |
| "S-iban", | |
| "B-tax_number", | |
| "I-tax_number", | |
| "E-tax_number", | |
| "S-tax_number", | |
| "B-passport_number", | |
| "I-passport_number", | |
| "E-passport_number", | |
| "S-passport_number", | |
| "B-license_plate", | |
| "I-license_plate", | |
| "E-license_plate", | |
| "S-license_plate", | |
| "B-credit_card", | |
| "I-credit_card", | |
| "E-credit_card", | |
| "S-credit_card", | |
| "B-health_data", | |
| "I-health_data", | |
| "E-health_data", | |
| "S-health_data", | |
| "B-biometric_data", | |
| "I-biometric_data", | |
| "E-biometric_data", | |
| "S-biometric_data", | |
| "B-genetic_data", | |
| "I-genetic_data", | |
| "E-genetic_data", | |
| "S-genetic_data", | |
| "B-religion_or_belief", | |
| "I-religion_or_belief", | |
| "E-religion_or_belief", | |
| "S-religion_or_belief", | |
| "B-political_opinion", | |
| "I-political_opinion", | |
| "E-political_opinion", | |
| "S-political_opinion", | |
| "B-union_membership", | |
| "I-union_membership", | |
| "E-union_membership", | |
| "S-union_membership", | |
| "B-criminal_record", | |
| "I-criminal_record", | |
| "E-criminal_record", | |
| "S-criminal_record", | |
| "B-child_data", | |
| "I-child_data", | |
| "E-child_data", | |
| "S-child_data" | |
| ], | |
| "num_attention_heads": 14, | |
| "num_experts": 128, | |
| "num_hidden_layers": 8, | |
| "num_key_value_heads": 2, | |
| "num_labels": 89, | |
| "param_dtype": "bfloat16", | |
| "rope_ntk_alpha": 1.0, | |
| "rope_ntk_beta": 32.0, | |
| "rope_scaling_factor": 32.0, | |
| "rope_theta": 150000, | |
| "sliding_window": 257, | |
| "span_class_names": [ | |
| "O", | |
| "private_person", | |
| "private_email", | |
| "private_phone", | |
| "private_address", | |
| "private_date", | |
| "private_url", | |
| "account_number", | |
| "secret", | |
| "tckn", | |
| "iban", | |
| "tax_number", | |
| "passport_number", | |
| "license_plate", | |
| "credit_card", | |
| "health_data", | |
| "biometric_data", | |
| "genetic_data", | |
| "religion_or_belief", | |
| "political_opinion", | |
| "union_membership", | |
| "criminal_record", | |
| "child_data" | |
| ], | |
| "vocab_size": 200064 | |
| } | |