# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("tner/xlm-roberta-large-panx-dataset-en")
model = AutoModelForTokenClassification.from_pretrained("tner/xlm-roberta-large-panx-dataset-en", device_map="auto")Quick Links
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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-large-panx-dataset-en")
model = AutoModelForTokenClassification.from_pretrained("asahi417/tner-xlm-roberta-large-panx-dataset-en")
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="tner/xlm-roberta-large-panx-dataset-en")