Fill-Mask
Transformers
PyTorch
Safetensors
Russian
English
bert
pretraining
russian
embeddings
masked-lm
tiny
feature-extraction
sentence-similarity
Instructions to use cointegrated/rubert-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cointegrated/rubert-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="cointegrated/rubert-tiny")# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("cointegrated/rubert-tiny") model = AutoModelForPreTraining.from_pretrained("cointegrated/rubert-tiny") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3dbc5c389afd9e4c42b28c3d83c5e167edf2d334281a92159d0ac085f408a99f
- Size of remote file:
- 1.28 MB
- SHA256:
- 293b9dd69b63439316c4ad2747c28104b9ed61ef1dfc235b80726d507e3ca621
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