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{
  "_name_or_path": "TimSchopf/nlp_survey_classifier",
  "adapters": {
    "adapters": {},
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    "fusion_config_map": {},
    "fusions": {}
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  "architectures": [
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    "3": "Information Extraction & Text Mining",
    "4": "Responsible & Trustworthy NLP",
    "5": "Numerical Reasoning",
    "6": "Phonology",
    "7": "Code-Switching",
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    "14": "Dialogue Response Generation",
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    "26": "Text Error Correction",
    "27": "Question Answering",
    "28": "Syntactic Parsing",
    "29": "Text Clustering",
    "30": "Summarization",
    "31": "Event Extraction",
    "32": "Paraphrasing",
    "33": "Polarity Analysis",
    "34": "Named Entity Recognition",
    "35": "Text Style Transfer",
    "36": "Text Classification",
    "37": "Machine Reading Comprehension",
    "38": "Dialogue Systems & Conversational Agents",
    "39": "Captioning",
    "40": "Semantic Parsing",
    "41": "Semantic Search",
    "42": "Text Complexity",
    "43": "Chunking",
    "44": "Code Generation",
    "45": "Typology",
    "46": "Fact & Claim Verification",
    "47": "Text Generation",
    "48": "Linguistics & Cognitive NLP",
    "49": "Opinion Mining",
    "50": "Structured Data in NLP",
    "51": "Machine Translation",
    "52": "Language Models",
    "53": "Semantic Similarity",
    "54": "Knowledge Graph Reasoning",
    "55": "Programming Languages in NLP",
    "56": "Document Retrieval",
    "57": "Linguistic Theories",
    "58": "Robustness in NLP",
    "59": "Text Normalization",
    "60": "Argument Mining",
    "61": "Emotion Analysis",
    "62": "Commonsense Reasoning",
    "63": "Tagging",
    "64": "Phonetics",
    "65": "Word Sense Disambiguation",
    "66": "Passage Retrieval",
    "67": "Stylistic Analysis",
    "68": "Green & Sustainable NLP",
    "69": "Indexing",
    "70": "Speech & Audio in NLP",
    "71": "Discourse & Pragmatics",
    "72": "Semantic Text Processing",
    "73": "Morphology",
    "74": "Multimodality",
    "75": "Relation Extraction",
    "76": "Question Generation",
    "77": "Psycholinguistics",
    "78": "Sentiment Analysis",
    "79": "Intent Recognition",
    "80": "Low-Resource NLP",
    "81": "Explainability & Interpretability in NLP"
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    "Programming Languages in NLP": 55,
    "Psycholinguistics": 77,
    "Question Answering": 27,
    "Question Generation": 76,
    "Reasoning": 8,
    "Relation Extraction": 75,
    "Representation Learning": 12,
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    "Robustness in NLP": 58,
    "Semantic Parsing": 40,
    "Semantic Search": 41,
    "Semantic Similarity": 53,
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    "Sentiment Analysis": 78,
    "Speech & Audio in NLP": 70,
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    "Stylistic Analysis": 67,
    "Summarization": 30,
    "Syntactic Parsing": 28,
    "Syntactic Text Processing": 15,
    "Tagging": 63,
    "Term Extraction": 1,
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    "Text Clustering": 29,
    "Text Complexity": 42,
    "Text Error Correction": 26,
    "Text Generation": 47,
    "Text Normalization": 59,
    "Text Segmentation": 21,
    "Text Style Transfer": 35,
    "Textual Inference": 22,
    "Topic Modeling": 9,
    "Typology": 45,
    "Visual Data in NLP": 20,
    "Word Sense Disambiguation": 65
  },
  "layer_norm_eps": 1e-12,
  "max_position_embeddings": 512,
  "model_type": "bert",
  "num_attention_heads": 12,
  "num_hidden_layers": 12,
  "pad_token_id": 0,
  "position_embedding_type": "absolute",
  "problem_type": "multi_label_classification",
  "torch_dtype": "float32",
  "transformers_version": "4.24.0",
  "type_vocab_size": 2,
  "use_cache": true,
  "vocab_size": 31090
}