Instructions to use DimasikKurd/MedRuRobertaLarge_pos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DimasikKurd/MedRuRobertaLarge_pos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="DimasikKurd/MedRuRobertaLarge_pos")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("DimasikKurd/MedRuRobertaLarge_pos") model = AutoModelForTokenClassification.from_pretrained("DimasikKurd/MedRuRobertaLarge_pos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- de75738ee9866e73b963d4b7a6e9e3b11abaed16394d861b6e51697d39bf0236
- Size of remote file:
- 4.92 kB
- SHA256:
- 23f78cd38a18a6b9b7f1a5ed6d02ad059d4b15b5fb28109d6bd679df12f28f14
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