Instructions to use rmihaylov/bert-base-ner-theseus-bg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rmihaylov/bert-base-ner-theseus-bg with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="rmihaylov/bert-base-ner-theseus-bg")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("rmihaylov/bert-base-ner-theseus-bg") model = AutoModelForTokenClassification.from_pretrained("rmihaylov/bert-base-ner-theseus-bg", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from rmihaylov/bert-base-ner-theseus-bg: direct link, hf CLI and curl.
- Browser
- Download file 583 Bytes
-
https://huggingface.co/rmihaylov/bert-base-ner-theseus-bg/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://rmihaylov/bert-base-ner-theseus-bg/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/rmihaylov/bert-base-ner-theseus-bg/resolve/main/tokenizer_config.json
583 Bytes
| {"do_lower_case": false, "remove_space": true, "keep_accents": true, "bos_token": "[CLS]", "eos_token": "[SEP]", "unk_token": "<unk>", "sep_token": "[SEP]", "pad_token": "<pad>", "cls_token": "[CLS]", "mask_token": {"content": "[MASK]", "single_word": false, "lstrip": true, "rstrip": false, "normalized": false, "__type": "AddedToken"}, "sp_model_kwargs": {}, "model_max_length": 128, "special_tokens_map_file": "/content/drive/MyDrive/ColabModels/MBERT_NER_THESEUS/pytorch_model/special_tokens_map.json", "name_or_path": "/content/tokenizer/", "tokenizer_class": "AlbertTokenizer"} |