Instructions to use ArtCad98/eubert_covid_ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArtCad98/eubert_covid_ft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ArtCad98/eubert_covid_ft")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ArtCad98/eubert_covid_ft") model = AutoModelForMaskedLM.from_pretrained("ArtCad98/eubert_covid_ft") - Notebooks
- Google Colab
- Kaggle
Delete tokenizer_config (1).json
Browse files- tokenizer_config (1).json +0 -110
tokenizer_config (1).json
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{
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"add_prefix_space": false,
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"added_tokens_decoder": {
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"0": {
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"content": "[UNK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"1": {
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"content": "[PAD]",
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"lstrip": false,
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"normalized": false,
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"single_word": false,
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"special": true
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"2": {
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"single_word": false,
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"special": true
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"3": {
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"content": "[SEP]",
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"single_word": false,
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"special": true
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"lstrip": true,
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"single_word": false,
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"special": true
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"special": true
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"content": "<unk>",
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"content": "<pad>",
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"content": "<mask>",
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"special": true
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}
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},
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"additional_special_tokens": [
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"[UNK]",
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"[PAD]",
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"[CLS]",
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"<unk>",
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"<pad>",
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"<mask>"
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],
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"bos_token": "[CLS]",
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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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"eos_token": "[SEP]",
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"errors": "replace",
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"mask_token": "[MASK]",
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"max_len": 512,
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"model_max_length": 512,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"tokenizer_class": "RobertaTokenizer",
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"trim_offsets": true,
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"unk_token": "[UNK]"
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}
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