Token Classification
Transformers
PyTorch
TensorBoard
Safetensors
Russian
bert
Generated from Trainer
named-entity-recognition
russian
ner
Eval Results (legacy)
Instructions to use viktoroo/sberbank-rubert-base-collection3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use viktoroo/sberbank-rubert-base-collection3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="viktoroo/sberbank-rubert-base-collection3")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("viktoroo/sberbank-rubert-base-collection3") model = AutoModelForTokenClassification.from_pretrained("viktoroo/sberbank-rubert-base-collection3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a8d1d01598419c702770711ab07d66af578cf1b6cfdd9926cc0a42763b6f536
- Size of remote file:
- 711 MB
- SHA256:
- 5ce02a23c24e7816ccfaa876b4f410c36cc7d7e81ffa5e7a237d38cc5fb5208a
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