Fill-Mask
Transformers
PyTorch
English
roberta
NER
named entity recognition
RE
relation extraction
entity mention detection
EMD
coreference resolution
Instructions to use aiola/roberta-base-corener with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aiola/roberta-base-corener with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="aiola/roberta-base-corener")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("aiola/roberta-base-corener") model = AutoModelForMaskedLM.from_pretrained("aiola/roberta-base-corener") - Notebooks
- Google Colab
- Kaggle
File size: 373 Bytes
ab48119 | 1 | {"errors": "replace", "bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": "<mask>", "add_prefix_space": false, "trim_offsets": true, "do_lower_case": false, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "roberta-base", "tokenizer_class": "RobertaTokenizer"} |