Instructions to use eleldar/rubert-base-cased-sentence with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eleldar/rubert-base-cased-sentence with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="eleldar/rubert-base-cased-sentence")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("eleldar/rubert-base-cased-sentence") model = AutoModel.from_pretrained("eleldar/rubert-base-cased-sentence", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c7d64a639df2229db64bfd8cfb201dcbdce03ca302401c8fe10ddc1b2b2126ab
- Size of remote file:
- 711 MB
- SHA256:
- b9cbb490313afeacc1f62def5cdfdf2541736f65e1bf5c6fb7f017210139359c
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