Instructions to use Tatiana239/lilt-ruroberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tatiana239/lilt-ruroberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Tatiana239/lilt-ruroberta")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Tatiana239/lilt-ruroberta") model = AutoModelForTokenClassification.from_pretrained("Tatiana239/lilt-ruroberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a4d1b7446f6751b81a3366a024c873f7597c04baab065c1741edcf294cb37277
- Size of remote file:
- 3.44 kB
- SHA256:
- 4d1cb23dea7952bbfd4df367624c4545dfc5abc88a55c9c03a706d4e36264342
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