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")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("aiola/roberta-large-corener") model = AutoModelForMaskedLM.from_pretrained("aiola/roberta-large-corener") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a62a806dce33ad32981c954d321c676c6a9cb4e1fb3d4caf5b556189111c8182
- Size of remote file:
- 1.47 GB
- SHA256:
- e13f5750100ba9332c830fc9efb1d56b6d881df0d435600940fff1117362d8eb
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