Token Classification
Transformers
Safetensors
deberta-v2
named-entity-recognition
ner
multilingual
slavic
mdeberta-v3
iob2
Eval Results (legacy)
Instructions to use ivlcic/snerta-8l-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ivlcic/snerta-8l-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ivlcic/snerta-8l-base")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ivlcic/snerta-8l-base") model = AutoModelForTokenClassification.from_pretrained("ivlcic/snerta-8l-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ea7716d1d671706d1f36051d2cd8051101b0a30ecc8187424e1573e4470ffaec
- Size of remote file:
- 5.33 kB
- SHA256:
- dcbf2ce0596bbf5ccd6ffb042b9191c63682ff8832ab038882bf211fd75518c5
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