Text Classification
Transformers
TensorBoard
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use orpe42/deberta_MP_dynamic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use orpe42/deberta_MP_dynamic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="orpe42/deberta_MP_dynamic")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("orpe42/deberta_MP_dynamic") model = AutoModelForSequenceClassification.from_pretrained("orpe42/deberta_MP_dynamic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download current_best/config.json from orpe42/deberta_MP_dynamic: direct link, hf CLI and curl.
- Browser
- Download file 5.15 kB
-
https://huggingface.co/orpe42/deberta_MP_dynamic/resolve/main/current_best/config.json
- Command line
-
hf download hf://orpe42/deberta_MP_dynamic/current_best/config.json
-
curl -L -o config.json https://huggingface.co/orpe42/deberta_MP_dynamic/resolve/main/current_best/config.json
5.15 kB
| { | |
| "architectures": [ | |
| "DebertaV2ForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": null, | |
| "dtype": "float32", | |
| "eos_token_id": null, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 1024, | |
| "id2label": { | |
| "101": "FOREIGN_SPECIAL_RELATIONS_POSITIVE", | |
| "102": "FOREIGN_SPECIAL_RELATIONS_NEGATIVE", | |
| "103": "ANTI_IMPERIALISM", | |
| "104": "MILITARY_POSITIVE", | |
| "105": "MILITARY_NEGATIVE", | |
| "106": "PEACE", | |
| "107": "INTERNATIONALISM_POSITIVE", | |
| "108": "EUROPEAN_INTEGRATION_POSITIVE", | |
| "109": "INTERNATIONALISM_NEGATIVE", | |
| "110": "EUROPEAN_INTEGRATION_NEGATIVE", | |
| "201": "FREEDOM_HUMAN_RIGHTS", | |
| "202": "DEMOCRACY_GENERAL", | |
| "203": "CONSTITUTIONALISM_POSITIVE", | |
| "204": "CONSTITUTIONALISM_NEGATIVE", | |
| "301": "DECENTRALISATION_POSITIVE", | |
| "302": "CENTRALISATION_POSITIVE", | |
| "303": "GOVERNMENTAL_EFFICIENCY_POSITIVE", | |
| "304": "POLITICAL_CORRUPTION_NEGATIVE", | |
| "305": "POLITICAL_AUTHORITY", | |
| "401": "FREE_ENTERPRISE_POSITIVE", | |
| "402": "INCENTIVES_POSITIVE", | |
| "403": "MARKET_REGULATION", | |
| "404": "ECONOMIC_PLANNING", | |
| "405": "CORPORATISM_MIXED_ECONOMY", | |
| "406": "PROTECTIONISM_POSITIVE", | |
| "407": "PROTECTIONISM_NEGATIVE", | |
| "408": "ECONOMIC_GOALS", | |
| "409": "KEYNESIAN_DEMAND_MANAGEMENT", | |
| "410": "PRODUCTIVITY", | |
| "411": "TECHNOLOGY_AND_INFRASTRUCTURE", | |
| "412": "CONTROLLED_ECONOMY", | |
| "413": "NATIONALISATION", | |
| "414": "ECONOMIC_ORTHODOXY", | |
| "415": "MARXIST_ANALYSIS", | |
| "416": "ANTI_GROWTH_ECONOMY_POSITIVE", | |
| "501": "ENVIRONMENTAL_PROTECTION", | |
| "502": "CULTURE", | |
| "503": "SOCIAL_JUSTICE", | |
| "504": "WELFARE_STATE_EXPANSION", | |
| "505": "WELFARE_STATE_LIMITATION", | |
| "506": "EDUCATION_EXPANSION", | |
| "507": "EDUCATION_LIMITATION", | |
| "601": "NATIONAL_WAY_OF_LIFE_POSITIVE", | |
| "602": "NATIONAL_WAY_OF_LIFE_NEGATIVE", | |
| "603": "TRADITIONAL_MORALITY_POSITIVE", | |
| "604": "TRADITIONAL_MORALITY_NEGATIVE", | |
| "605": "LAW_AND_ORDER", | |
| "606": "CIVIC_MINDEDNESS", | |
| "607": "MULTICULTURALISM_GENERAL_POSITIVE", | |
| "608": "MULTICULTURALISM_GENERAL_NEGATIVE", | |
| "701": "LABOUR_GROUPS_POSITIVE", | |
| "702": "LABOUR_GROUPS_NEGATIVE", | |
| "703": "AGRICULTURE_AND_FARMERS", | |
| "704": "MIDDLE_CLASS_AND_PROFESSIONALS", | |
| "705": "UNDERPRIVILEGED_MINORITY_GROUPS", | |
| "706": "NON_ECONOMIC_DEMOGRAPHIC_GROUPS" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 4096, | |
| "label2id": { | |
| "AGRICULTURE_AND_FARMERS": 703, | |
| "ANTI_GROWTH_ECONOMY_POSITIVE": 416, | |
| "ANTI_IMPERIALISM": 103, | |
| "CENTRALISATION_POSITIVE": 302, | |
| "CIVIC_MINDEDNESS": 606, | |
| "CONSTITUTIONALISM_NEGATIVE": 204, | |
| "CONSTITUTIONALISM_POSITIVE": 203, | |
| "CONTROLLED_ECONOMY": 412, | |
| "CORPORATISM_MIXED_ECONOMY": 405, | |
| "CULTURE": 502, | |
| "DECENTRALISATION_POSITIVE": 301, | |
| "DEMOCRACY_GENERAL": 202, | |
| "ECONOMIC_GOALS": 408, | |
| "ECONOMIC_ORTHODOXY": 414, | |
| "ECONOMIC_PLANNING": 404, | |
| "EDUCATION_EXPANSION": 506, | |
| "EDUCATION_LIMITATION": 507, | |
| "ENVIRONMENTAL_PROTECTION": 501, | |
| "EUROPEAN_INTEGRATION_NEGATIVE": 110, | |
| "EUROPEAN_INTEGRATION_POSITIVE": 108, | |
| "FOREIGN_SPECIAL_RELATIONS_NEGATIVE": 102, | |
| "FOREIGN_SPECIAL_RELATIONS_POSITIVE": 101, | |
| "FREEDOM_HUMAN_RIGHTS": 201, | |
| "FREE_ENTERPRISE_POSITIVE": 401, | |
| "GOVERNMENTAL_EFFICIENCY_POSITIVE": 303, | |
| "INCENTIVES_POSITIVE": 402, | |
| "INTERNATIONALISM_NEGATIVE": 109, | |
| "INTERNATIONALISM_POSITIVE": 107, | |
| "KEYNESIAN_DEMAND_MANAGEMENT": 409, | |
| "LABOUR_GROUPS_NEGATIVE": 702, | |
| "LABOUR_GROUPS_POSITIVE": 701, | |
| "LAW_AND_ORDER": 605, | |
| "MARKET_REGULATION": 403, | |
| "MARXIST_ANALYSIS": 415, | |
| "MIDDLE_CLASS_AND_PROFESSIONALS": 704, | |
| "MILITARY_NEGATIVE": 105, | |
| "MILITARY_POSITIVE": 104, | |
| "MULTICULTURALISM_GENERAL_NEGATIVE": 608, | |
| "MULTICULTURALISM_GENERAL_POSITIVE": 607, | |
| "NATIONALISATION": 413, | |
| "NATIONAL_WAY_OF_LIFE_NEGATIVE": 602, | |
| "NATIONAL_WAY_OF_LIFE_POSITIVE": 601, | |
| "NON_ECONOMIC_DEMOGRAPHIC_GROUPS": 706, | |
| "PEACE": 106, | |
| "POLITICAL_AUTHORITY": 305, | |
| "POLITICAL_CORRUPTION_NEGATIVE": 304, | |
| "PRODUCTIVITY": 410, | |
| "PROTECTIONISM_NEGATIVE": 407, | |
| "PROTECTIONISM_POSITIVE": 406, | |
| "SOCIAL_JUSTICE": 503, | |
| "TECHNOLOGY_AND_INFRASTRUCTURE": 411, | |
| "TRADITIONAL_MORALITY_NEGATIVE": 604, | |
| "TRADITIONAL_MORALITY_POSITIVE": 603, | |
| "UNDERPRIVILEGED_MINORITY_GROUPS": 705, | |
| "WELFARE_STATE_EXPANSION": 504, | |
| "WELFARE_STATE_LIMITATION": 505 | |
| }, | |
| "layer_norm_eps": 1e-07, | |
| "legacy": true, | |
| "max_position_embeddings": 512, | |
| "max_relative_positions": -1, | |
| "model_type": "deberta-v2", | |
| "norm_rel_ebd": "layer_norm", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 24, | |
| "pad_token_id": 0, | |
| "pooler_dropout": 0.0, | |
| "pooler_hidden_act": "gelu", | |
| "pooler_hidden_size": 1024, | |
| "pos_att_type": [ | |
| "p2c", | |
| "c2p" | |
| ], | |
| "position_biased_input": false, | |
| "position_buckets": 256, | |
| "problem_type": "multi_label_classification", | |
| "relative_attention": true, | |
| "share_att_key": true, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.12.1", | |
| "type_vocab_size": 0, | |
| "use_cache": false, | |
| "vocab_size": 128100 | |
| } | |