Token Classification
Transformers
PyTorch
TensorBoard
Safetensors
Russian
bert
Generated from Trainer
named-entity-recognition
russian
ner
Eval Results (legacy)
Instructions to use viktor-shcherb/sberbank-rubert-base-collection3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use viktor-shcherb/sberbank-rubert-base-collection3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="viktor-shcherb/sberbank-rubert-base-collection3")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("viktor-shcherb/sberbank-rubert-base-collection3") model = AutoModelForTokenClassification.from_pretrained("viktor-shcherb/sberbank-rubert-base-collection3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
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