Token Classification
Transformers
PyTorch
Slovak
roberta
Generated from Trainer
Eval Results (legacy)
Instructions to use crabz/slovakbert-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use crabz/slovakbert-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="crabz/slovakbert-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("crabz/slovakbert-ner") model = AutoModelForTokenClassification.from_pretrained("crabz/slovakbert-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5215c4deb0a8251951d48b3e3699a2eaf3131886362a82eec6953c002d101a13
- Size of remote file:
- 496 MB
- SHA256:
- 9fbd8a2479c99e55f5906e5e46438562b27e5b5ec36829d0216824b91d41d690
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