Instructions to use vbolshakov/RuLUKE-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vbolshakov/RuLUKE-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="vbolshakov/RuLUKE-tiny")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("vbolshakov/RuLUKE-tiny") model = AutoModel.from_pretrained("vbolshakov/RuLUKE-tiny") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b174454a4d49db34091ed23cc3c7e0abf3b2dc3e8dc93edf6df34930167d50fc
- Size of remote file:
- 635 MB
- SHA256:
- 22840d6e4bd30742c9d4228cb3e746fa3ab659f9fa0328c84dd770b982c7142a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.