Token Classification
Transformers
Safetensors
deberta-v2
named-entity-recognition
ner
multilingual
slavic
mdeberta-v3
iob2
Eval Results (legacy)
Instructions to use ivlcic/snerta-12l-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ivlcic/snerta-12l-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ivlcic/snerta-12l-base")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ivlcic/snerta-12l-base") model = AutoModelForTokenClassification.from_pretrained("ivlcic/snerta-12l-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a86576cfc2d3ad472ec46ddd0f6b8d150bce85ff4528d03cb9938ed5c93fee6a
- Size of remote file:
- 16 MB
- SHA256:
- f1fc0fc3d7f208e8d9fd9c9a4e5ebf62075b0603f9ae58b34df09e7eb5991e88
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