Instructions to use DimasikKurd/rubert-base-cased_pos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DimasikKurd/rubert-base-cased_pos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="DimasikKurd/rubert-base-cased_pos")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("DimasikKurd/rubert-base-cased_pos") model = AutoModelForTokenClassification.from_pretrained("DimasikKurd/rubert-base-cased_pos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 391ca0bb49f78454ab49d2f86710033d8861e83aabeae85235349da5d9518f11
- Size of remote file:
- 4.92 kB
- SHA256:
- c6e27668f3e3911dc83c65d3909dab27b86be209896b32f27e01cfe63960fb65
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