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:
- dbaa88dad71241118295768d7728b1efa42b779b2f4612d6e846e25864c93794
- Size of remote file:
- 640 kB
- SHA256:
- d6afde64def093a9d493d1f4254768c2e842ed45bcc9c184233f245cb29d2a31
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