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README.md
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- **Demo (Coming soon)
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## Uses
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'DiagLab': 'Diagnostisch und Laborverfahren',
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'LabValues': 'Klinisches Attribut',
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'HealthState': 'Gesunder Zustand',
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'Process': 'Physiologische Funktion',
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'TimeInfo': 'Zeitliches Konzept'}
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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- **Demo (Coming soon)
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## Uses
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import sys
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sys.path.append('modules')
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import torch
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from transformers import AutoConfig, AutoTokenizer, AutoModelForMaskedLM, EncoderDecoderConfig
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from BERT2span_semantic_disam import BERT2span
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from helpers import load_config, set_seed
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from inference import final_label_results_rescaled
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base_name = "bert-base-german-cased"
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configs = load_config('configs/step3_gpu_span_semantic_group.yaml')
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tokenizer = AutoTokenizer.from_pretrained(base_name)
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bertMLM = AutoModelForMaskedLM.from_pretrained(base_name)
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bert_sner = BERT2span(configs, bertMLM, tokenizer)
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checkpoint_path = "checkpoints/german_bert_ex4cds_500_semantic_term.ckpt"
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state_dict = torch.load(checkpoint_path, map_location=torch.device('cpu'))
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bert_sner.load_state_dict(state_dict)
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bert_sner.eval()
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suggested_terms = {'Condition': 'Zeichen oder Symptom',
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'DiagLab': 'Diagnostisch und Laborverfahren',
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'LabValues': 'Klinisches Attribut',
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'HealthState': 'Gesunder Zustand',
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'Process': 'Physiologische Funktion',
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'TimeInfo': 'Zeitliches Konzept'}
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words = "Aktuell Infekt mit Nachweis von E Coli und Pseudomonas im TBS- CRP 99mg/dl".split()
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words_list = [words]
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heatmaps, ner_results = final_label_results_rescaled(words_list, tokenizer, berst_sner, suggested_terms, threshold=0.5)
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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