Upload Nemotron v2 privacy-filter checkpoint

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,215 @@
+---
+license: other
+library_name: transformers
+base_model: openai/privacy-filter
+pipeline_tag: token-classification
+tags:
+  - privacy
+  - pii
+  - ner
+  - token-classification
+  - redaction
+  - nemotron
+  - openmed
+  - openai-privacy-filter
+language:
+  - bg
+  - cs
+  - da
+  - de
+  - el
+  - en
+  - es
+  - et
+  - fi
+  - fr
+  - hr
+  - hu
+  - it
+  - lt
+  - lv
+  - nl
+  - pl
+  - pt
+  - ro
+  - sk
+datasets:
+  - nvidia/Nemotron-PII
+  - gretelai/gretel-pii-masking-en-v1
+  - ai4privacy/pii-masking-openpii-1m
+private: true
+---
+
+# privacy-filter-nemotron-v2
+
+`OpenMed/privacy-filter-nemotron-v2` is the second-generation
+Nemotron-schema checkpoint in the OpenMed privacy-filter family. It keeps the
+same fine-grained 55-category PII vocabulary as
+`OpenMed/privacy-filter-nemotron`, while using a broader training mix and a
+more recall-oriented adaptation recipe. In practice, this v2 checkpoint should
+perform better as a general PII masking and redaction model while preserving
+the useful typed labels from the original Nemotron model.
+
+The model is based on `openai/privacy-filter`, a 1.4B-parameter MoE token
+classifier with roughly 50M active parameters per token. It predicts 221 BIOES
+token classes:
+
+- `O`
+- 55 PII categories encoded as `B-*`, `I-*`, `E-*`, and `S-*`
+
+Use this checkpoint when you want the Nemotron fine-grained label schema, but
+prefer the improved v2 masking behavior.
+
+## Relationship To The Original Nemotron Model
+
+This model is a direct successor to `OpenMed/privacy-filter-nemotron`.
+
+- Same base architecture: `openai/privacy-filter`
+- Same core label schema: 55 fine-grained Nemotron-style PII categories
+- Same output format: BIOES token classification
+- Broader adaptation data: Nemotron-style fine labels plus additional PII
+  masking examples from other synthetic PII sources
+- Better practical masking behavior for general redaction use cases
+
+The original `OpenMed/privacy-filter-nemotron` remains useful when you want the
+cleanest single-dataset Nemotron training lineage. This v2 model is the better
+default when you want stronger general-purpose PII masking while keeping the
+same fine-grained schema.
+
+## Quick Start
+
+### With OpenMed
+
+```bash
+pip install -U "openmed[hf]"
+```
+
+```python
+from openmed import extract_pii, deidentify
+
+model_name = "OpenMed/privacy-filter-nemotron-v2"
+text = (
+    "Patient Sarah Johnson (DOB 03/15/1985), MRN 4872910, "
+    "phone 415-555-0123, email sarah.johnson@example.com."
+)
+
+result = extract_pii(text, model_name=model_name)
+for ent in result.entities:
+    print(ent.label, ent.text)
+
+masked = deidentify(text, method="mask", model_name=model_name)
+print(masked.deidentified_text)
+```
+
+### With `opf`
+
+```bash
+pip install 'opf @ git+https://github.com/openai/privacy-filter.git'
+
+opf redact \
+  --checkpoint OpenMed/privacy-filter-nemotron-v2 \
+  --text "Patient Sarah Johnson (DOB 03/15/1985), MRN 4872910, phone 415-555-0123."
+```
+
+### With Transformers
+
+```python
+from transformers import AutoModelForTokenClassification, AutoTokenizer, pipeline
+
+repo_id = "OpenMed/privacy-filter-nemotron-v2"
+
+tokenizer = AutoTokenizer.from_pretrained(repo_id, trust_remote_code=True)
+model = AutoModelForTokenClassification.from_pretrained(
+    repo_id,
+    trust_remote_code=True,
+)
+
+ner = pipeline(
+    "token-classification",
+    model=model,
+    tokenizer=tokenizer,
+    aggregation_strategy="simple",
+)
+
+text = "Patient Sarah Johnson, MRN 4872910, can be reached at sarah@example.com."
+print(ner(text))
+```
+
+For best production behavior, use BIOES-aware decoding and merge overlapping or
+consecutive spans before masking.
+
+## Label Space
+
+The checkpoint uses 55 fine-grained PII categories:
+
+- Identity and demographic attributes: `first_name`, `last_name`, `age`,
+  `gender`, `race_ethnicity`, `sexuality`, `religious_belief`,
+  `political_view`, `marital_status`, `nationality`, `education_level`,
+  `occupation`, `employment_status`, `language`, `blood_type`,
+  `biometric_identifier`
+- Contact and web identifiers: `email`, `phone_number`, `fax_number`, `url`
+- Address: `street_address`, `city`, `county`, `state`, `country`, `postcode`,
+  `coordinate`
+- Dates and times: `date`, `date_of_birth`, `date_time`, `time`
+- Government and regulated IDs: `ssn`, `national_id`, `tax_id`
+- Financial and secret values: `account_number`, `bank_routing_number`,
+  `swift_bic`, `credit_debit_card`, `cvv`, `pin`, `password`
+- Healthcare identifiers: `medical_record_number`,
+  `health_plan_beneficiary_number`
+- Enterprise and customer identifiers: `customer_id`, `employee_id`,
+  `unique_id`, `certificate_license_number`
+- Vehicle identifiers: `license_plate`, `vehicle_identifier`
+- Digital identifiers: `ipv4`, `ipv6`, `mac_address`, `device_identifier`,
+  `api_key`, `http_cookie`
+
+The full label-space JSON is included as `label_space_fine_v1.json`.
+
+## Training Summary
+
+This checkpoint was initialized from the first-generation OpenMed Nemotron
+privacy-filter branch and further adapted with source-balanced typed PII
+examples.
+
+- Base model: `openai/privacy-filter`
+- First-generation predecessor: `OpenMed/privacy-filter-nemotron`
+- Output schema: 55 fine-grained PII labels, 221 BIOES classes
+- Training precision: bf16
+- Training method: full fine-tuning with OpenAI's `opf train`
+
+The training mix includes synthetic PII examples derived from:
+
+- `nvidia/Nemotron-PII`
+- `gretelai/gretel-pii-masking-en-v1`
+- `ai4privacy/pii-masking-openpii-1m`
+
+## Limitations And Intended Use
+
+This is an experimental private checkpoint intended for PII detection,
+masking, and de-identification workflows. It should be validated on your target
+domain before use in high-stakes systems.
+
+For clinical PHI, radiology/DICOM workflows, legal data, or other regulated
+settings, use this model as one component inside a broader de-identification
+pipeline with deterministic rules, audit logging, and human review where
+appropriate.
+
+## Credits
+
+This model builds on:
+
+- OpenAI's `openai/privacy-filter` model and `opf` training tools
+- NVIDIA's `nvidia/Nemotron-PII`
+- Gretel's `gretelai/gretel-pii-masking-en-v1`
+- AI4Privacy's `ai4privacy/pii-masking-openpii-1m`
+
+## Citation
+
+```bibtex
+@misc{openmed_privacy_filter_nemotron_v2_2026,
+  author       = {OpenMed},
+  title        = {{OpenMed/privacy-filter-nemotron-v2}: second-generation Nemotron-schema privacy filter},
+  year         = {2026},
+  publisher    = {Hugging Face},
+  howpublished = {\url{https://huggingface.co/OpenMed/privacy-filter-nemotron-v2}}
+}
+```

config.json

@@ -0,0 +1,783 @@
+{
+  "architectures": [
+    "OpenAIPrivacyFilterForTokenClassification"
+  ],
+  "attention_bias": true,
+  "attention_dropout": 0.0,
+  "bos_token_id": null,
+  "classifier_dropout": 0.0,
+  "default_n_ctx": 128000,
+  "dtype": "bfloat16",
+  "eos_token_id": 199999,
+  "head_dim": 64,
+  "hidden_act": "silu",
+  "hidden_size": 640,
+  "id2label": {
+    "0": "O",
+    "1": "B-account_number",
+    "2": "I-account_number",
+    "3": "E-account_number",
+    "4": "S-account_number",
+    "5": "B-age",
+    "6": "I-age",
+    "7": "E-age",
+    "8": "S-age",
+    "9": "B-api_key",
+    "10": "I-api_key",
+    "11": "E-api_key",
+    "12": "S-api_key",
+    "13": "B-bank_routing_number",
+    "14": "I-bank_routing_number",
+    "15": "E-bank_routing_number",
+    "16": "S-bank_routing_number",
+    "17": "B-biometric_identifier",
+    "18": "I-biometric_identifier",
+    "19": "E-biometric_identifier",
+    "20": "S-biometric_identifier",
+    "21": "B-blood_type",
+    "22": "I-blood_type",
+    "23": "E-blood_type",
+    "24": "S-blood_type",
+    "25": "B-certificate_license_number",
+    "26": "I-certificate_license_number",
+    "27": "E-certificate_license_number",
+    "28": "S-certificate_license_number",
+    "29": "B-city",
+    "30": "I-city",
+    "31": "E-city",
+    "32": "S-city",
+    "33": "B-company_name",
+    "34": "I-company_name",
+    "35": "E-company_name",
+    "36": "S-company_name",
+    "37": "B-coordinate",
+    "38": "I-coordinate",
+    "39": "E-coordinate",
+    "40": "S-coordinate",
+    "41": "B-country",
+    "42": "I-country",
+    "43": "E-country",
+    "44": "S-country",
+    "45": "B-county",
+    "46": "I-county",
+    "47": "E-county",
+    "48": "S-county",
+    "49": "B-credit_debit_card",
+    "50": "I-credit_debit_card",
+    "51": "E-credit_debit_card",
+    "52": "S-credit_debit_card",
+    "53": "B-customer_id",
+    "54": "I-customer_id",
+    "55": "E-customer_id",
+    "56": "S-customer_id",
+    "57": "B-cvv",
+    "58": "I-cvv",
+    "59": "E-cvv",
+    "60": "S-cvv",
+    "61": "B-date",
+    "62": "I-date",
+    "63": "E-date",
+    "64": "S-date",
+    "65": "B-date_of_birth",
+    "66": "I-date_of_birth",
+    "67": "E-date_of_birth",
+    "68": "S-date_of_birth",
+    "69": "B-date_time",
+    "70": "I-date_time",
+    "71": "E-date_time",
+    "72": "S-date_time",
+    "73": "B-device_identifier",
+    "74": "I-device_identifier",
+    "75": "E-device_identifier",
+    "76": "S-device_identifier",
+    "77": "B-education_level",
+    "78": "I-education_level",
+    "79": "E-education_level",
+    "80": "S-education_level",
+    "81": "B-email",
+    "82": "I-email",
+    "83": "E-email",
+    "84": "S-email",
+    "85": "B-employee_id",
+    "86": "I-employee_id",
+    "87": "E-employee_id",
+    "88": "S-employee_id",
+    "89": "B-employment_status",
+    "90": "I-employment_status",
+    "91": "E-employment_status",
+    "92": "S-employment_status",
+    "93": "B-fax_number",
+    "94": "I-fax_number",
+    "95": "E-fax_number",
+    "96": "S-fax_number",
+    "97": "B-first_name",
+    "98": "I-first_name",
+    "99": "E-first_name",
+    "100": "S-first_name",
+    "101": "B-gender",
+    "102": "I-gender",
+    "103": "E-gender",
+    "104": "S-gender",
+    "105": "B-health_plan_beneficiary_number",
+    "106": "I-health_plan_beneficiary_number",
+    "107": "E-health_plan_beneficiary_number",
+    "108": "S-health_plan_beneficiary_number",
+    "109": "B-http_cookie",
+    "110": "I-http_cookie",
+    "111": "E-http_cookie",
+    "112": "S-http_cookie",
+    "113": "B-ipv4",
+    "114": "I-ipv4",
+    "115": "E-ipv4",
+    "116": "S-ipv4",
+    "117": "B-ipv6",
+    "118": "I-ipv6",
+    "119": "E-ipv6",
+    "120": "S-ipv6",
+    "121": "B-language",
+    "122": "I-language",
+    "123": "E-language",
+    "124": "S-language",
+    "125": "B-last_name",
+    "126": "I-last_name",
+    "127": "E-last_name",
+    "128": "S-last_name",
+    "129": "B-license_plate",
+    "130": "I-license_plate",
+    "131": "E-license_plate",
+    "132": "S-license_plate",
+    "133": "B-mac_address",
+    "134": "I-mac_address",
+    "135": "E-mac_address",
+    "136": "S-mac_address",
+    "137": "B-medical_record_number",
+    "138": "I-medical_record_number",
+    "139": "E-medical_record_number",
+    "140": "S-medical_record_number",
+    "141": "B-national_id",
+    "142": "I-national_id",
+    "143": "E-national_id",
+    "144": "S-national_id",
+    "145": "B-occupation",
+    "146": "I-occupation",
+    "147": "E-occupation",
+    "148": "S-occupation",
+    "149": "B-password",
+    "150": "I-password",
+    "151": "E-password",
+    "152": "S-password",
+    "153": "B-phone_number",
+    "154": "I-phone_number",
+    "155": "E-phone_number",
+    "156": "S-phone_number",
+    "157": "B-pin",
+    "158": "I-pin",
+    "159": "E-pin",
+    "160": "S-pin",
+    "161": "B-political_view",
+    "162": "I-political_view",
+    "163": "E-political_view",
+    "164": "S-political_view",
+    "165": "B-postcode",
+    "166": "I-postcode",
+    "167": "E-postcode",
+    "168": "S-postcode",
+    "169": "B-race_ethnicity",
+    "170": "I-race_ethnicity",
+    "171": "E-race_ethnicity",
+    "172": "S-race_ethnicity",
+    "173": "B-religious_belief",
+    "174": "I-religious_belief",
+    "175": "E-religious_belief",
+    "176": "S-religious_belief",
+    "177": "B-sexuality",
+    "178": "I-sexuality",
+    "179": "E-sexuality",
+    "180": "S-sexuality",
+    "181": "B-ssn",
+    "182": "I-ssn",
+    "183": "E-ssn",
+    "184": "S-ssn",
+    "185": "B-state",
+    "186": "I-state",
+    "187": "E-state",
+    "188": "S-state",
+    "189": "B-street_address",
+    "190": "I-street_address",
+    "191": "E-street_address",
+    "192": "S-street_address",
+    "193": "B-swift_bic",
+    "194": "I-swift_bic",
+    "195": "E-swift_bic",
+    "196": "S-swift_bic",
+    "197": "B-tax_id",
+    "198": "I-tax_id",
+    "199": "E-tax_id",
+    "200": "S-tax_id",
+    "201": "B-time",
+    "202": "I-time",
+    "203": "E-time",
+    "204": "S-time",
+    "205": "B-unique_id",
+    "206": "I-unique_id",
+    "207": "E-unique_id",
+    "208": "S-unique_id",
+    "209": "B-url",
+    "210": "I-url",
+    "211": "E-url",
+    "212": "S-url",
+    "213": "B-user_name",
+    "214": "I-user_name",
+    "215": "E-user_name",
+    "216": "S-user_name",
+    "217": "B-vehicle_identifier",
+    "218": "I-vehicle_identifier",
+    "219": "E-vehicle_identifier",
+    "220": "S-vehicle_identifier"
+  },
+  "initial_context_length": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 640,
+  "label2id": {
+    "O": 0,
+    "B-account_number": 1,
+    "I-account_number": 2,
+    "E-account_number": 3,
+    "S-account_number": 4,
+    "B-age": 5,
+    "I-age": 6,
+    "E-age": 7,
+    "S-age": 8,
+    "B-api_key": 9,
+    "I-api_key": 10,
+    "E-api_key": 11,
+    "S-api_key": 12,
+    "B-bank_routing_number": 13,
+    "I-bank_routing_number": 14,
+    "E-bank_routing_number": 15,
+    "S-bank_routing_number": 16,
+    "B-biometric_identifier": 17,
+    "I-biometric_identifier": 18,
+    "E-biometric_identifier": 19,
+    "S-biometric_identifier": 20,
+    "B-blood_type": 21,
+    "I-blood_type": 22,
+    "E-blood_type": 23,
+    "S-blood_type": 24,
+    "B-certificate_license_number": 25,
+    "I-certificate_license_number": 26,
+    "E-certificate_license_number": 27,
+    "S-certificate_license_number": 28,
+    "B-city": 29,
+    "I-city": 30,
+    "E-city": 31,
+    "S-city": 32,
+    "B-company_name": 33,
+    "I-company_name": 34,
+    "E-company_name": 35,
+    "S-company_name": 36,
+    "B-coordinate": 37,
+    "I-coordinate": 38,
+    "E-coordinate": 39,
+    "S-coordinate": 40,
+    "B-country": 41,
+    "I-country": 42,
+    "E-country": 43,
+    "S-country": 44,
+    "B-county": 45,
+    "I-county": 46,
+    "E-county": 47,
+    "S-county": 48,
+    "B-credit_debit_card": 49,
+    "I-credit_debit_card": 50,
+    "E-credit_debit_card": 51,
+    "S-credit_debit_card": 52,
+    "B-customer_id": 53,
+    "I-customer_id": 54,
+    "E-customer_id": 55,
+    "S-customer_id": 56,
+    "B-cvv": 57,
+    "I-cvv": 58,
+    "E-cvv": 59,
+    "S-cvv": 60,
+    "B-date": 61,
+    "I-date": 62,
+    "E-date": 63,
+    "S-date": 64,
+    "B-date_of_birth": 65,
+    "I-date_of_birth": 66,
+    "E-date_of_birth": 67,
+    "S-date_of_birth": 68,
+    "B-date_time": 69,
+    "I-date_time": 70,
+    "E-date_time": 71,
+    "S-date_time": 72,
+    "B-device_identifier": 73,
+    "I-device_identifier": 74,
+    "E-device_identifier": 75,
+    "S-device_identifier": 76,
+    "B-education_level": 77,
+    "I-education_level": 78,
+    "E-education_level": 79,
+    "S-education_level": 80,
+    "B-email": 81,
+    "I-email": 82,
+    "E-email": 83,
+    "S-email": 84,
+    "B-employee_id": 85,
+    "I-employee_id": 86,
+    "E-employee_id": 87,
+    "S-employee_id": 88,
+    "B-employment_status": 89,
+    "I-employment_status": 90,
+    "E-employment_status": 91,
+    "S-employment_status": 92,
+    "B-fax_number": 93,
+    "I-fax_number": 94,
+    "E-fax_number": 95,
+    "S-fax_number": 96,
+    "B-first_name": 97,
+    "I-first_name": 98,
+    "E-first_name": 99,
+    "S-first_name": 100,
+    "B-gender": 101,
+    "I-gender": 102,
+    "E-gender": 103,
+    "S-gender": 104,
+    "B-health_plan_beneficiary_number": 105,
+    "I-health_plan_beneficiary_number": 106,
+    "E-health_plan_beneficiary_number": 107,
+    "S-health_plan_beneficiary_number": 108,
+    "B-http_cookie": 109,
+    "I-http_cookie": 110,
+    "E-http_cookie": 111,
+    "S-http_cookie": 112,
+    "B-ipv4": 113,
+    "I-ipv4": 114,
+    "E-ipv4": 115,
+    "S-ipv4": 116,
+    "B-ipv6": 117,
+    "I-ipv6": 118,
+    "E-ipv6": 119,
+    "S-ipv6": 120,
+    "B-language": 121,
+    "I-language": 122,
+    "E-language": 123,
+    "S-language": 124,
+    "B-last_name": 125,
+    "I-last_name": 126,
+    "E-last_name": 127,
+    "S-last_name": 128,
+    "B-license_plate": 129,
+    "I-license_plate": 130,
+    "E-license_plate": 131,
+    "S-license_plate": 132,
+    "B-mac_address": 133,
+    "I-mac_address": 134,
+    "E-mac_address": 135,
+    "S-mac_address": 136,
+    "B-medical_record_number": 137,
+    "I-medical_record_number": 138,
+    "E-medical_record_number": 139,
+    "S-medical_record_number": 140,
+    "B-national_id": 141,
+    "I-national_id": 142,
+    "E-national_id": 143,
+    "S-national_id": 144,
+    "B-occupation": 145,
+    "I-occupation": 146,
+    "E-occupation": 147,
+    "S-occupation": 148,
+    "B-password": 149,
+    "I-password": 150,
+    "E-password": 151,
+    "S-password": 152,
+    "B-phone_number": 153,
+    "I-phone_number": 154,
+    "E-phone_number": 155,
+    "S-phone_number": 156,
+    "B-pin": 157,
+    "I-pin": 158,
+    "E-pin": 159,
+    "S-pin": 160,
+    "B-political_view": 161,
+    "I-political_view": 162,
+    "E-political_view": 163,
+    "S-political_view": 164,
+    "B-postcode": 165,
+    "I-postcode": 166,
+    "E-postcode": 167,
+    "S-postcode": 168,
+    "B-race_ethnicity": 169,
+    "I-race_ethnicity": 170,
+    "E-race_ethnicity": 171,
+    "S-race_ethnicity": 172,
+    "B-religious_belief": 173,
+    "I-religious_belief": 174,
+    "E-religious_belief": 175,
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+    "B-street_address": 189,
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+      "account_number",
+      "age",
+      "api_key",
+      "bank_routing_number",
+      "biometric_identifier",
+      "blood_type",
+      "certificate_license_number",
+      "city",
+      "company_name",
+      "coordinate",
+      "country",
+      "county",
+      "credit_debit_card",
+      "customer_id",
+      "cvv",
+      "date",
+      "date_of_birth",
+      "date_time",
+      "device_identifier",
+      "education_level",
+      "email",
+      "employee_id",
+      "employment_status",
+      "fax_number",
+      "first_name",
+      "gender",
+      "health_plan_beneficiary_number",
+      "http_cookie",
+      "ipv4",
+      "ipv6",
+      "language",
+      "last_name",
+      "license_plate",
+      "mac_address",
+      "medical_record_number",
+      "national_id",
+      "occupation",
+      "password",
+      "phone_number",
+      "pin",
+      "political_view",
+      "postcode",
+      "race_ethnicity",
+      "religious_belief",
+      "sexuality",
+      "ssn",
+      "state",
+      "street_address",
+      "swift_bic",
+      "tax_id",
+      "time",
+      "unique_id",
+      "url",
+      "user_name",
+      "vehicle_identifier"
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+      "B-account_number",
+      "I-account_number",
+      "E-account_number",
+      "S-account_number",
+      "B-age",
+      "I-age",
+      "E-age",
+      "S-age",
+      "B-api_key",
+      "I-api_key",
+      "E-api_key",
+      "S-api_key",
+      "B-bank_routing_number",
+      "I-bank_routing_number",
+      "E-bank_routing_number",
+      "S-bank_routing_number",
+      "B-biometric_identifier",
+      "I-biometric_identifier",
+      "E-biometric_identifier",
+      "S-biometric_identifier",
+      "B-blood_type",
+      "I-blood_type",
+      "E-blood_type",
+      "S-blood_type",
+      "B-certificate_license_number",
+      "I-certificate_license_number",
+      "E-certificate_license_number",
+      "S-certificate_license_number",
+      "B-city",
+      "I-city",
+      "E-city",
+      "S-city",
+      "B-company_name",
+      "I-company_name",
+      "E-company_name",
+      "S-company_name",
+      "B-coordinate",
+      "I-coordinate",
+      "E-coordinate",
+      "S-coordinate",
+      "B-country",
+      "I-country",
+      "E-country",
+      "S-country",
+      "B-county",
+      "I-county",
+      "E-county",
+      "S-county",
+      "B-credit_debit_card",
+      "I-credit_debit_card",
+      "E-credit_debit_card",
+      "S-credit_debit_card",
+      "B-customer_id",
+      "I-customer_id",
+      "E-customer_id",
+      "S-customer_id",
+      "B-cvv",
+      "I-cvv",
+      "E-cvv",
+      "S-cvv",
+      "B-date",
+      "I-date",
+      "E-date",
+      "S-date",
+      "B-date_of_birth",
+      "I-date_of_birth",
+      "E-date_of_birth",
+      "S-date_of_birth",
+      "B-date_time",
+      "I-date_time",
+      "E-date_time",
+      "S-date_time",
+      "B-device_identifier",
+      "I-device_identifier",
+      "E-device_identifier",
+      "S-device_identifier",
+      "B-education_level",
+      "I-education_level",
+      "E-education_level",
+      "S-education_level",
+      "B-email",
+      "I-email",
+      "E-email",
+      "S-email",
+      "B-employee_id",
+      "I-employee_id",
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+      "S-employee_id",
+      "B-employment_status",
+      "I-employment_status",
+      "E-employment_status",
+      "S-employment_status",
+      "B-fax_number",
+      "I-fax_number",
+      "E-fax_number",
+      "S-fax_number",
+      "B-first_name",
+      "I-first_name",
+      "E-first_name",
+      "S-first_name",
+      "B-gender",
+      "I-gender",
+      "E-gender",
+      "S-gender",
+      "B-health_plan_beneficiary_number",
+      "I-health_plan_beneficiary_number",
+      "E-health_plan_beneficiary_number",
+      "S-health_plan_beneficiary_number",
+      "B-http_cookie",
+      "I-http_cookie",
+      "E-http_cookie",
+      "S-http_cookie",
+      "B-ipv4",
+      "I-ipv4",
+      "E-ipv4",
+      "S-ipv4",
+      "B-ipv6",
+      "I-ipv6",
+      "E-ipv6",
+      "S-ipv6",
+      "B-language",
+      "I-language",
+      "E-language",
+      "S-language",
+      "B-last_name",
+      "I-last_name",
+      "E-last_name",
+      "S-last_name",
+      "B-license_plate",
+      "I-license_plate",
+      "E-license_plate",
+      "S-license_plate",
+      "B-mac_address",
+      "I-mac_address",
+      "E-mac_address",
+      "S-mac_address",
+      "B-medical_record_number",
+      "I-medical_record_number",
+      "E-medical_record_number",
+      "S-medical_record_number",
+      "B-national_id",
+      "I-national_id",
+      "E-national_id",
+      "S-national_id",
+      "B-occupation",
+      "I-occupation",
+      "E-occupation",
+      "S-occupation",
+      "B-password",
+      "I-password",
+      "E-password",
+      "S-password",
+      "B-phone_number",
+      "I-phone_number",
+      "E-phone_number",
+      "S-phone_number",
+      "B-pin",
+      "I-pin",
+      "E-pin",
+      "S-pin",
+      "B-political_view",
+      "I-political_view",
+      "E-political_view",
+      "S-political_view",
+      "B-postcode",
+      "I-postcode",
+      "E-postcode",
+      "S-postcode",
+      "B-race_ethnicity",
+      "I-race_ethnicity",
+      "E-race_ethnicity",
+      "S-race_ethnicity",
+      "B-religious_belief",
+      "I-religious_belief",
+      "E-religious_belief",
+      "S-religious_belief",
+      "B-sexuality",
+      "I-sexuality",
+      "E-sexuality",
+      "S-sexuality",
+      "B-ssn",
+      "I-ssn",
+      "E-ssn",
+      "S-ssn",
+      "B-state",
+      "I-state",
+      "E-state",
+      "S-state",
+      "B-street_address",
+      "I-street_address",
+      "E-street_address",
+      "S-street_address",
+      "B-swift_bic",
+      "I-swift_bic",
+      "E-swift_bic",
+      "S-swift_bic",
+      "B-tax_id",
+      "I-tax_id",
+      "E-tax_id",
+      "S-tax_id",
+      "B-time",
+      "I-time",
+      "E-time",
+      "S-time",
+      "B-unique_id",
+      "I-unique_id",
+      "E-unique_id",
+      "S-unique_id",
+      "B-url",
+      "I-url",
+      "E-url",
+      "S-url",
+      "B-user_name",
+      "I-user_name",
+      "E-user_name",
+      "S-user_name",
+      "B-vehicle_identifier",
+      "I-vehicle_identifier",
+      "E-vehicle_identifier",
+      "S-vehicle_identifier"
+    ],
+    "inference_contract_version": 1
+  }
+}

label_space_fine_v1.json

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+{
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+  "span_class_names": [
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+    "account_number",
+    "age",
+    "api_key",
+    "bank_routing_number",
+    "biometric_identifier",
+    "blood_type",
+    "certificate_license_number",
+    "city",
+    "company_name",
+    "coordinate",
+    "country",
+    "county",
+    "credit_debit_card",
+    "customer_id",
+    "cvv",
+    "date",
+    "date_of_birth",
+    "date_time",
+    "device_identifier",
+    "education_level",
+    "email",
+    "employee_id",
+    "employment_status",
+    "fax_number",
+    "first_name",
+    "gender",
+    "health_plan_beneficiary_number",
+    "http_cookie",
+    "ipv4",
+    "ipv6",
+    "language",
+    "last_name",
+    "license_plate",
+    "mac_address",
+    "medical_record_number",
+    "national_id",
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+    "password",
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+    "sexuality",
+    "ssn",
+    "state",
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+    "swift_bic",
+    "tax_id",
+    "time",
+    "unique_id",
+    "url",
+    "user_name",
+    "vehicle_identifier"
+  ]
+}

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tokenizer_config.json

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+}