Instructions to use tner/xlm-roberta-base-wnut2017 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tner/xlm-roberta-base-wnut2017 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="tner/xlm-roberta-base-wnut2017")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("tner/xlm-roberta-base-wnut2017") model = AutoModelForTokenClassification.from_pretrained("tner/xlm-roberta-base-wnut2017") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
XLM-RoBERTa for NER
XLM-RoBERTa finetuned on NER. Check more detail at TNER repository.
Usage
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("asahi417/tner-xlm-roberta-base-wnut2017")
model = AutoModelForTokenClassification.from_pretrained("asahi417/tner-xlm-roberta-base-wnut2017")
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