Instructions to use UMCU/MedRoBERTa.nl_NegationDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UMCU/MedRoBERTa.nl_NegationDetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="UMCU/MedRoBERTa.nl_NegationDetection")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("UMCU/MedRoBERTa.nl_NegationDetection") model = AutoModelForTokenClassification.from_pretrained("UMCU/MedRoBERTa.nl_NegationDetection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from UMCU/MedRoBERTa.nl_NegationDetection: direct link, hf CLI and curl.
- Browser
- Download file 1.19 kB
-
https://huggingface.co/UMCU/MedRoBERTa.nl_NegationDetection/resolve/main/tokenizer_config.json
- Command line
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hf download hf://UMCU/MedRoBERTa.nl_NegationDetection/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/UMCU/MedRoBERTa.nl_NegationDetection/resolve/main/tokenizer_config.json
1.19 kB
| {"unk_token": {"content": "<unk>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "eos_token": {"content": "</s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "add_prefix_space": false, "errors": "replace", "sep_token": {"content": "</s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "cls_token": {"content": "<s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "pad_token": {"content": "<pad>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "special_tokens_map_file": null, "name_or_path": "/media/koekiemonster/DATA-FAST/text_data/word_vectors_and_language_models/dutch/Medical/languagemodels/MedRoBERTa", "tokenizer_class": "RobertaTokenizer"} |