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
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- embeddings
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- masked-lm
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- tiny
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license: mit
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widget:
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- text: "Миниатюрная модель для [MASK] разных задач."
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- embeddings
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- masked-lm
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- tiny
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- feature-extraction
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- sentence-similarity
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license: mit
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widget:
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- text: "Миниатюрная модель для [MASK] разных задач."
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