Instructions to use DimasikKurd/sbert_large_nlu_ru_pos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DimasikKurd/sbert_large_nlu_ru_pos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="DimasikKurd/sbert_large_nlu_ru_pos")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("DimasikKurd/sbert_large_nlu_ru_pos") model = AutoModelForTokenClassification.from_pretrained("DimasikKurd/sbert_large_nlu_ru_pos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c58ad866f05de6217b7b8dc569d372889781688c3fe615e4b1ede2f2fa81188e
- Size of remote file:
- 4.92 kB
- SHA256:
- 3059ffff252517bd3173806ccdc8aac0bf87d0b7938bb58a31538770afd2f7c4
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