Upload ModernBertForTokenClassification

README.md

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+---
+library_name: transformers
+tags: []
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
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+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
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+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
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+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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+[More Information Needed]
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+### Downstream Use [optional]
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+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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+[More Information Needed]
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+### Out-of-Scope Use
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+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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+[More Information Needed]
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+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
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+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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+[More Information Needed]
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+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
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+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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+[More Information Needed]
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+#### Metrics
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+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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+[More Information Needed]
+
+### Results
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+[More Information Needed]
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+#### Summary
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+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
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+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
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+[More Information Needed]
+
+### Compute Infrastructure
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+[More Information Needed]
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+#### Hardware
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+[More Information Needed]
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+#### Software
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+[More Information Needed]
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+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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+**BibTeX:**
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+[More Information Needed]
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+**APA:**
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+[More Information Needed]
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+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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+[More Information Needed]
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+## More Information [optional]
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+[More Information Needed]
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+## Model Card Authors [optional]
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+[More Information Needed]
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+## Model Card Contact
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+[More Information Needed]

config.json

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+{
+  "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": "bfloat16",
+  "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": 768,
+  "id2label": {
+    "0": "O",
+    "1": "B-account_number",
+    "2": "B-age",
+    "3": "B-api_key",
+    "4": "B-bank_routing_number",
+    "5": "B-biometric_identifier",
+    "6": "B-blood_type",
+    "7": "B-certificate_license_number",
+    "8": "B-city",
+    "9": "B-company_name",
+    "10": "B-coordinate",
+    "11": "B-country",
+    "12": "B-county",
+    "13": "B-credit_debit_card",
+    "14": "B-customer_id",
+    "15": "B-cvv",
+    "16": "B-date",
+    "17": "B-date_of_birth",
+    "18": "B-date_time",
+    "19": "B-device_identifier",
+    "20": "B-education_level",
+    "21": "B-email",
+    "22": "B-employee_id",
+    "23": "B-employment_status",
+    "24": "B-fax_number",
+    "25": "B-first_name",
+    "26": "B-gender",
+    "27": "B-health_plan_beneficiary_number",
+    "28": "B-http_cookie",
+    "29": "B-ipv4",
+    "30": "B-ipv6",
+    "31": "B-language",
+    "32": "B-last_name",
+    "33": "B-license_plate",
+    "34": "B-mac_address",
+    "35": "B-medical_record_number",
+    "36": "B-occupation",
+    "37": "B-password",
+    "38": "B-phone_number",
+    "39": "B-pin",
+    "40": "B-political_view",
+    "41": "B-postcode",
+    "42": "B-race_ethnicity",
+    "43": "B-religious_belief",
+    "44": "B-sexuality",
+    "45": "B-ssn",
+    "46": "B-state",
+    "47": "B-street_address",
+    "48": "B-swift_bic",
+    "49": "B-tax_id",
+    "50": "B-time",
+    "51": "B-unique_id",
+    "52": "B-url",
+    "53": "B-user_name",
+    "54": "B-vehicle_identifier",
+    "55": "I-account_number",
+    "56": "I-age",
+    "57": "I-api_key",
+    "58": "I-bank_routing_number",
+    "59": "I-biometric_identifier",
+    "60": "I-blood_type",
+    "61": "I-certificate_license_number",
+    "62": "I-city",
+    "63": "I-company_name",
+    "64": "I-coordinate",
+    "65": "I-country",
+    "66": "I-county",
+    "67": "I-credit_debit_card",
+    "68": "I-customer_id",
+    "69": "I-cvv",
+    "70": "I-date",
+    "71": "I-date_of_birth",
+    "72": "I-date_time",
+    "73": "I-device_identifier",
+    "74": "I-education_level",
+    "75": "I-email",
+    "76": "I-employee_id",
+    "77": "I-employment_status",
+    "78": "I-fax_number",
+    "79": "I-first_name",
+    "80": "I-gender",
+    "81": "I-health_plan_beneficiary_number",
+    "82": "I-http_cookie",
+    "83": "I-ipv4",
+    "84": "I-ipv6",
+    "85": "I-language",
+    "86": "I-last_name",
+    "87": "I-license_plate",
+    "88": "I-mac_address",
+    "89": "I-medical_record_number",
+    "90": "I-occupation",
+    "91": "I-password",
+    "92": "I-phone_number",
+    "93": "I-pin",
+    "94": "I-political_view",
+    "95": "I-postcode",
+    "96": "I-race_ethnicity",
+    "97": "I-religious_belief",
+    "98": "I-sexuality",
+    "99": "I-ssn",
+    "100": "I-state",
+    "101": "I-street_address",
+    "102": "I-swift_bic",
+    "103": "I-tax_id",
+    "104": "I-time",
+    "105": "I-unique_id",
+    "106": "I-url",
+    "107": "I-user_name",
+    "108": "I-vehicle_identifier"
+  },
+  "initializer_cutoff_factor": 2.0,
+  "initializer_range": 0.02,
+  "intermediate_size": 1152,
+  "label2id": {
+    "B-account_number": 1,
+    "B-age": 2,
+    "B-api_key": 3,
+    "B-bank_routing_number": 4,
+    "B-biometric_identifier": 5,
+    "B-blood_type": 6,
+    "B-certificate_license_number": 7,
+    "B-city": 8,
+    "B-company_name": 9,
+    "B-coordinate": 10,
+    "B-country": 11,
+    "B-county": 12,
+    "B-credit_debit_card": 13,
+    "B-customer_id": 14,
+    "B-cvv": 15,
+    "B-date": 16,
+    "B-date_of_birth": 17,
+    "B-date_time": 18,
+    "B-device_identifier": 19,
+    "B-education_level": 20,
+    "B-email": 21,
+    "B-employee_id": 22,
+    "B-employment_status": 23,
+    "B-fax_number": 24,
+    "B-first_name": 25,
+    "B-gender": 26,
+    "B-health_plan_beneficiary_number": 27,
+    "B-http_cookie": 28,
+    "B-ipv4": 29,
+    "B-ipv6": 30,
+    "B-language": 31,
+    "B-last_name": 32,
+    "B-license_plate": 33,
+    "B-mac_address": 34,
+    "B-medical_record_number": 35,
+    "B-occupation": 36,
+    "B-password": 37,
+    "B-phone_number": 38,
+    "B-pin": 39,
+    "B-political_view": 40,
+    "B-postcode": 41,
+    "B-race_ethnicity": 42,
+    "B-religious_belief": 43,
+    "B-sexuality": 44,
+    "B-ssn": 45,
+    "B-state": 46,
+    "B-street_address": 47,
+    "B-swift_bic": 48,
+    "B-tax_id": 49,
+    "B-time": 50,
+    "B-unique_id": 51,
+    "B-url": 52,
+    "B-user_name": 53,
+    "B-vehicle_identifier": 54,
+    "I-account_number": 55,
+    "I-age": 56,
+    "I-api_key": 57,
+    "I-bank_routing_number": 58,
+    "I-biometric_identifier": 59,
+    "I-blood_type": 60,
+    "I-certificate_license_number": 61,
+    "I-city": 62,
+    "I-company_name": 63,
+    "I-coordinate": 64,
+    "I-country": 65,
+    "I-county": 66,
+    "I-credit_debit_card": 67,
+    "I-customer_id": 68,
+    "I-cvv": 69,
+    "I-date": 70,
+    "I-date_of_birth": 71,
+    "I-date_time": 72,
+    "I-device_identifier": 73,
+    "I-education_level": 74,
+    "I-email": 75,
+    "I-employee_id": 76,
+    "I-employment_status": 77,
+    "I-fax_number": 78,
+    "I-first_name": 79,
+    "I-gender": 80,
+    "I-health_plan_beneficiary_number": 81,
+    "I-http_cookie": 82,
+    "I-ipv4": 83,
+    "I-ipv6": 84,
+    "I-language": 85,
+    "I-last_name": 86,
+    "I-license_plate": 87,
+    "I-mac_address": 88,
+    "I-medical_record_number": 89,
+    "I-occupation": 90,
+    "I-password": 91,
+    "I-phone_number": 92,
+    "I-pin": 93,
+    "I-political_view": 94,
+    "I-postcode": 95,
+    "I-race_ethnicity": 96,
+    "I-religious_belief": 97,
+    "I-sexuality": 98,
+    "I-ssn": 99,
+    "I-state": 100,
+    "I-street_address": 101,
+    "I-swift_bic": 102,
+    "I-tax_id": 103,
+    "I-time": 104,
+    "I-unique_id": 105,
+    "I-url": 106,
+    "I-user_name": 107,
+    "I-vehicle_identifier": 108,
+    "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": 12,
+  "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
+}

model.safetensors

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