pytorch xlm-roberta token-classification transformers
.gitattributes README.md config.json parameter.json pytorch_model.bin sentencepiece.bpe.model special_tokens_map.json test_bc5cdr_span_lower.json test_bionlp2004_span_lower.json test_conll2003_span_lower.json test_fin_span_lower.json test_mit_movie_trivia_lower.json test_mit_movie_trivia_span_lower.json test_mit_restaurant_span_lower.json test_ontonotes5_span_lower.json test_panx_dataset-en_span_lower.json test_wnut2017_span_lower.json tokenizer_config.json
# XLM-RoBERTa for NER
XLM-RoBERTa finetuned on NER. Check more detail at [TNER repository](https://github.com/asahi417/tner).

## Usage
```
  from transformers import AutoTokenizer, AutoModelForTokenClassification
  
  tokenizer = AutoTokenizer.from_pretrained("asahi417/tner-xlm-roberta-base-uncased-mit-movie-trivia")
  
  model = AutoModelForTokenClassification.from_pretrained("asahi417/tner-xlm-roberta-base-uncased-mit-movie-trivia")
 ```