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
File size: 373 Bytes
b0d45fb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"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>"
}
|