Token Classification
Transformers
PyTorch
xlm-roberta
text
named entity recognition
roberta
historical languages
precision
recall
Eval Results (legacy)
Instructions to use magistermilitum/roberta-multilingual-medieval-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use magistermilitum/roberta-multilingual-medieval-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="magistermilitum/roberta-multilingual-medieval-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("magistermilitum/roberta-multilingual-medieval-ner") model = AutoModelForTokenClassification.from_pretrained("magistermilitum/roberta-multilingual-medieval-ner") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#6 opened about 1 year ago
by
SFconvertbot
Training Data
#5 opened almost 2 years ago
by
wjbmattingly
Adding `safetensors` variant of this model
#4 opened over 2 years ago
by
SFconvertbot
Adding `safetensors` variant of this model
#3 opened about 3 years ago
by
SFconvertbot
Add multilingual to the language tag
#2 opened over 3 years ago
by
lbourdois
Update README.md
#1 opened over 3 years ago
by
lbourdois