Instructions to use imgreencucumber/rubert-ner-collection3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use imgreencucumber/rubert-ner-collection3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="imgreencucumber/rubert-ner-collection3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("imgreencucumber/rubert-ner-collection3") model = AutoModelForTokenClassification.from_pretrained("imgreencucumber/rubert-ner-collection3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload from https://github.com/imgreencucumber/ru-ner/commit/3da1f09c15be1c18a1907fba2b72f800c6e49d0e
bf9a7fa verified Download tokenizer_config.json from imgreencucumber/rubert-ner-collection3: direct link, hf CLI and curl.
- Browser
- Download file 395 Bytes
-
https://huggingface.co/imgreencucumber/rubert-ner-collection3/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://imgreencucumber/rubert-ner-collection3/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/imgreencucumber/rubert-ner-collection3/resolve/main/tokenizer_config.json
395 Bytes
| { | |
| "backend": "tokenizers", | |
| "cls_token": "[CLS]", | |
| "do_lower_case": false, | |
| "is_local": false, | |
| "local_files_only": false, | |
| "mask_token": "[MASK]", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "BertTokenizer", | |
| "unk_token": "[UNK]" | |
| } | |