Fill-Mask
Transformers
PyTorch
English
roberta
NER
named entity recognition
RE
relation extraction
entity mention detection
EMD
coreference resolution
Instructions to use aiola/roberta-large-corener with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aiola/roberta-large-corener with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="aiola/roberta-large-corener")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("aiola/roberta-large-corener") model = AutoModelForMaskedLM.from_pretrained("aiola/roberta-large-corener", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from aiola/roberta-large-corener: direct link, hf CLI and curl.
- Browser
- Download file 374 Bytes
-
https://huggingface.co/aiola/roberta-large-corener/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://aiola/roberta-large-corener/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/aiola/roberta-large-corener/resolve/main/tokenizer_config.json
374 Bytes
| {"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-large", "tokenizer_class": "RobertaTokenizer"} |