Instructions to use Davlan/xlm-roberta-base-ner-hrl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Davlan/xlm-roberta-base-ner-hrl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Davlan/xlm-roberta-base-ner-hrl")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Davlan/xlm-roberta-base-ner-hrl") model = AutoModelForTokenClassification.from_pretrained("Davlan/xlm-roberta-base-ner-hrl", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 69679dbbd7ec8352c462f1e5c746d7b862ebcd60ebf81ee0f22eaeed396e011d
- Size of remote file:
- 1.52 kB
- SHA256:
- 51cab81814224af5f90f3aa852cfac91b6203ac6bcfe6eabc7185f2fea5d7644
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