Token Classification
Transformers
PyTorch
Safetensors
Kazakh
xlm-roberta
Named Entity Recognition
NER
Instructions to use yeshpanovrustem/xlm-roberta-large-kaznerd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yeshpanovrustem/xlm-roberta-large-kaznerd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="yeshpanovrustem/xlm-roberta-large-kaznerd")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("yeshpanovrustem/xlm-roberta-large-kaznerd") model = AutoModelForTokenClassification.from_pretrained("yeshpanovrustem/xlm-roberta-large-kaznerd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8549bbcd92ee5c0795440e9474d628e32ec82df3c89808bc92ee2e53a5a5fe67
- Size of remote file:
- 2.24 GB
- SHA256:
- 2cc21ee2d3a19f0764a9f303865be844cb0fa3ad6c3dac933311181bbed36abb
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