Instructions to use zagibest/roberta-base-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zagibest/roberta-base-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="zagibest/roberta-base-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("zagibest/roberta-base-ner") model = AutoModelForTokenClassification.from_pretrained("zagibest/roberta-base-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from zagibest/roberta-base-ner: direct link, hf CLI and curl.
- Browser
- Download file 373 Bytes
-
https://huggingface.co/zagibest/roberta-base-ner/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://zagibest/roberta-base-ner/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/zagibest/roberta-base-ner/resolve/main/tokenizer_config.json
373 Bytes
| { | |
| "add_prefix_space": true, | |
| "bos_token": "<s>", | |
| "cls_token": "<s>", | |
| "eos_token": "</s>", | |
| "errors": "replace", | |
| "mask_token": "<mask>", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<pad>", | |
| "sep_token": "</s>", | |
| "special_tokens_map_file": null, | |
| "tokenizer_class": "RobertaTokenizer", | |
| "trim_offsets": true, | |
| "unk_token": "<unk>" | |
| } | |